Aberrant default mode network in amnestic mild cognitive impairment: a meta-analysis of independent component analysis studies

Lateralization of the Aberrant Amplitude of Low-Frequency Fluctuation within the Default Mode Network in Patients with Mild Cognitive Impairment

RATIONALE AND OBJECTIVES

Alzheimer's disease (AD) is the most common pathogenesis of dementia, and mild cognitive impairment (MCI) is considered as the intermediate stage from normal elderly to AD. Early detection of MCI is an essential step for the timely intervention of AD to slow the progression of this disease. Different form previous studies in the whole-brain spontaneous activities, this research aimed to explore the low-frequency amplitude spectrum activities of patients with MCI within the default mode network (DMN), which has been involved in the process of maintaining normal cognitive function.

MATERIALS AND METHODS

Based on resting-state functional magnetic resonance imaging, the amplitude of low-frequency fluctuation (ALFF) was used to analyze alterations in brain regions. The Mini-Mental State Examination and Montreal Cognitive Assessment were used for cognitive assessments. The correlation between imaging and behavioral results was analyzed among patients with MCI (n=36) and normal controls (n=26).

RESULTS

The DMN is the highest coverage of brain network regarding changes in local brain activity in patients with MCI. And the MCI group showed significant aberrant lateralization of the ALFF value.

CONCLUSION

The current results of our study has confirmed the hypothesis of cerebral functional impairment and compensation, and suggests that functional changes in the brain regions with reduced values of the ALFF occurred earlier than those with increased values. In a word, it suggested that the aberrant spontaneous brain activity in the DMN might be a specific imaging marker for improving MCI diagnoses.

Bibliometric analysis of functional magnetic resonance imaging studies on chronic pain over the past 20 years

PURPOSE

The utilization of functional magnetic resonance imaging (fMRI) in studying the mechanisms and treatment of chronic pain has gained significant popularity. However, there is currently a dearth of literature conducting bibliometric analysis on fMRI studies focused on chronic pain.

METHODS

All the literature included in this study was obtained from the Science Citation Index Expanded of Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze publications, authors, countries or regions, institutions, journals, references and keywords. Additionally, we evaluated the timeline and burst analysis of keywords, as well as the timeline and burst analysis of references. The search was conducted from 2004 to 2023 and completed within a single day on October 4th, 2023.

RESULTS

A total of 1,327 articles were retrieved. The annual publication shows an overall increasing trend. The United States has the highest number of publications and the main contributing institution is Harvard University. The journal PAIN produces the most articles. In recent years, resting-state fMRI, the prefrontal cortex, nucleus accumbens, thalamus, and migraines have been researched hotspots of fMRI studies on chronic pain.

CONCLUSIONS

This study provides an in-depth perspective on fMRI for chronic pain research, revealing key points, research hotspots and research trends, which offers valuable ideas for future research activities. It concludes with a summary of advances in clinical practice in this area, pointing out the need for critical evaluation of these findings in the light of guidelines and expert recommendations. It is anticipated that further high-quality research outputs will be generated in the future, which will facilitate the utilization of fMRI in clinical decision-making for chronic pain.

Studying the Alzheimer's disease continuum using EEG and fMRI in single-modality and multi-modality settings

Alzheimer's disease (AD) is a biological, clinical continuum that covers the preclinical, prodromal, and clinical phases of the disease. Early diagnosis and identification of the stages of Alzheimer's disease (AD) are crucial in clinical practice. Ideally, biomarkers should reflect the underlying process (pathological or otherwise), be reproducible and non-invasive, and allow repeated measurements over time. However, the currently known biomarkers for AD are not suitable for differentiating the stages and predicting the trajectory of disease progression. Some objective parameters extracted using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are widely applied to diagnose the stages of the AD continuum. While electroencephalography (EEG) has a high temporal resolution, fMRI has a high spatial resolution. Combined EEG and fMRI (EEG-fMRI) can overcome single-modality drawbacks and obtain multi-dimensional information simultaneously, and it can help explore the hemodynamic changes associated with the neural oscillations that occur during information processing. This technique has been used in the cognitive field in recent years. This review focuses on the different techniques available for studying the AD continuum, including EEG and fMRI in single-modality and multi-modality settings, and the possible future directions of AD diagnosis using EEG-fMRI.

Abnormalities of brain structure and function in cervical spondylosis: a multi-modal voxel-based meta-analysis

Background

Previous neuroimaging studies have revealed structural and functional brain abnormalities in patients with cervical spondylosis (CS). However, the results are divergent and inconsistent. Therefore, the present study conducted a multi-modal meta-analysis to investigate the consistent structural and functional brain alterations in CS patients.

Methods

A comprehensive literature search was conducted in five databases to retrieve relevant resting-state functional magnetic resonance imaging (rs-fMRI), structural MRI and diffusion tensor imaging (DTI) studies that measured brain functional and structural differences between CS patients and healthy controls (HCs). Separate and multimodal meta-analyses were implemented, respectively, by employing Anisotropic Effect-size Signed Differential Mapping software.

Results

13 rs-fMRI studies that used regional homogeneity, amplitude of low-frequency fluctuations (ALFF) and fractional ALFF, seven voxel-based morphometry (VBM) studies and one DTI study were finally included in the present research. However, no studies on surface-based morphometry (SBM) analysis were included in this research. Due to the insufficient number of SBM and DTI studies, only rs-fMRI and VBM meta-analyses were conducted. The results of rs-fMRI meta-analysis showed that compared to HCs, CS patients demonstrated decreased regional spontaneous brain activities in the right lingual gyrus, right middle temporal gyrus (MTG), left inferior parietal gyrus and right postcentral gyrus (PoCG), while increased activities in the right medial superior frontal gyrus, bilateral middle frontal gyrus and right precuneus. VBM meta-analysis detected increased GMV in the right superior temporal gyrus (STG) and right paracentral lobule (PCL), while decreased GMV in the left supplementary motor area and left MTG in CS patients. The multi-modal meta-analysis revealed increased GMV together with decreased regional spontaneous brain activity in the left PoCG, right STG and PCL among CS patients.

Conclusion

This meta-analysis revealed that compared to HCs, CS patients had significant alterations in GMV and regional spontaneous brain activity. The altered brain regions mainly included the primary visual cortex, the default mode network and the sensorimotor area, which may be associated with CS patients' symptoms of sensory deficits, blurred vision, cognitive impairment and motor dysfunction. The findings may contribute to understanding the underlying pathophysiology of brain dysfunction and provide references for early diagnosis and treatment of CS.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, CRD42022370967.

Altered functional connectivity of cerebellar subregions in male patients with obstructive sleep apnea: A resting-state fMRI study

PURPOSE

Previous studies have demonstrated impaired cerebellar function in patients with obstructive sleep apnea (OSA), which is associated with impaired cognition. However, the effects of OSA on resting-state functional connectivity (FC) in the cerebellum has not been determined. The purpose of this study was to investigate resting-state FC of the cerebellar subregions and its relevance to clinical symptoms in patients with OSA.

METHODS

Sixty-eight patients with OSA and seventy-two healthy controls (HCs) were included in the study. Eight subregions of the cerebellum were selected as regions of interest, and the FC values were calculated for each subregion with other voxels. A correlation analysis was performed to examine the relationship between clinical and cognitive data.

RESULTS

Patients with OSA showed higher FC in specific regions, including the right lobule VI with the right posterior middle temporal gyrus and right angular gyrus, the right Crus I with the bilateral precuneus/left superior parietal lobule, and the right Crus II with the precuneus/right posterior cingulate cortex. Furthermore, the oxygen depletion index was negatively correlated with aberrant FC between the right Crus II and the bilateral precuneus / right posterior cingulate cortex in OSA patients (p = 0.004).

CONCLUSION

The cerebellum is functionally lateralized and closely linked to the posterior default mode network. Higher FC is related to cognition, emotion, language, and sleep in OSA. Abnormal FC may offer new neuroimaging evidence and insights for a deeper comprehension of OSA-related alterations.

Identification of amnestic mild cognitive impairment by structural and functional MRI using a machine-learning approach

OBJECTIVE

The importance of early treatment for mild cognitive impairment (MCI) has been extensively shown. However, classifying patients presenting with memory complaints in clinical practice as having MCI vs normal results is difficult. Herein, we assessed the feasibility of applying a machine learning approach based on structural volumes and functional connectomic profiles to classify the cognitive levels of cognitively unimpaired (CU) and amnestic MCI (aMCI) groups. We further applied the same method to distinguish aMCI patients with a single memory impairment from those with multiple memory impairments.

METHODS

Fifty patients with aMCI were enrolled and classified as having either verbal or visual-aMCI (verbal or visual memory impairment), or both aMCI (verbal and visual memory impairments) based on memory test results. In addition, 26 CU patients were enrolled in the control group. All patients underwent structural T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. We obtained structural volumes and functional connectomic profiles from structural and functional MRI, respectively, using graph theory. A support vector machine (SVM) algorithm was employed, and k-fold cross-validation was performed to discriminate between groups.

RESULTS

The SVM classifier based on structural volumes revealed an accuracy of 88.9% at classifying the cognitive levels of patients with CU and aMCI. However, when the structural volumes and functional connectomic profiles were combined, the accuracy increased to 92.9%. In the classification of verbal or visual-aMCI (n = 22) versus both aMCI (n = 28), the SVM classifier based on structural volumes revealed a low accuracy of 36.7%. However, when the structural volumes and functional connectomic profiles were combined, the accuracy increased to 53.1%.

CONCLUSION

Structural volumes and functional connectomic profiles obtained using a machine learning approach can be used to classify cognitive levels to distinguish between aMCI and CU patients. In addition, combining the functional connectomic profiles with structural volumes results in a better classification performance than the use of structural volumes alone for identifying both "aMCI versus CU" and "verbal- or visual-aMCI versus both aMCI" patients.

Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer's disease

Alzheimer's disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.

Computerized Cognitive Training Enhances Episodic Memory by Down-Modulating Posterior Cingulate-Precuneus Connectivity in Older Persons With Mild Cognitive Impairment: A Randomized Controlled Trial

OBJECTIVE

The neural mechanisms underlying the beneficial effects of a computerized cognitive training (CCT) program for improving episodic memory in older persons with mild cognitive impairment (MCI) remain unclear. This study aimed to use both functional and structural brain changes to elucidate the treatment effects of CCT on enhancing episodic memory.

DESIGN, SETTING, AND PARTICIPANTS

Single-blinded, multicenter randomized controlled trial on 60 older adults with MCI in Fuzhou, China.

INTERVENTION

Participants were randomly assigned to either an 8-week 24-hour CCT program or a health education program as the control.

MEASUREMENTS

Clinical outcomes included changes in scores on the immediate and/or delayed recall subtests of the Chinese auditory verbal learning test (CAVLT) and rey complex figure test (CFT), and changes in gray matter volume and the functional connectivity of the posterior cingulate cortex (PCC) and hippocampus in the Papez circuit on magnetic resonance imaging.

RESULTS

Significant group-by-time effects showed greater improvements in both immediate and delayed recall scores of CAVLT and delayed recall scores of Rey CFT in participants receiving the CCT program compared to those in the health education program. Among the CCT participants, seed-based analyses revealed decreases in functional connectivity of the PCC and hippocampus with neural substrates in the parietal and occipital regions. The decreased PCC and precuneus connectivity were found to mediate patients' improvements in immediate recall function.

CONCLUSION

An 8-week CCT program was effective for improving episodic memory in older individuals with MCI. The decrease in connectivity originating from the PCC and hippocampus is suggestive of potential plastic changes in the Papez circuit, which could have alleviated the age-related compensatory mechanism. The findings of this study also shed light on expanding the content and extending the frequency and duration of the CCT program in future studies.

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.

Episodic Memory-Related Imaging Features as Valuable Biomarkers for the Diagnosis of Alzheimer's Disease: A Multicenter Study Based on Machine Learning

BACKGROUND

Individualized and reliable biomarkers are crucial for diagnosing Alzheimer's disease (AD). However, lack of accessibility and neurobiological correlation are the main obstacles to their clinical application. Machine learning algorithms can effectively identify personalized biomarkers based on the prominent symptoms of AD.

METHODS

Episodic memory-related magnetic resonance imaging (MRI) features of 143 patients with amnesic mild cognitive impairment (MCI) were identified using a multivariate relevance vector regression algorithm. The support vector machine classification model was constructed using these MRI features and verified in 2 independent datasets (N = 994). The neurobiological basis was also investigated based on cognitive assessments, neuropathologic biomarkers of cerebrospinal fluid, and positron emission tomography images of amyloid-β plaques.

RESULTS

The combination of gray matter volume and amplitude of low-frequency fluctuation MRI features accurately predicted episodic memory impairment in individual patients with amnesic MCI (r = 0.638) when measured using an episodic memory assessment panel. The MRI features that contributed to episodic memory prediction were primarily distributed across the default mode network and limbic network. The classification model based on these features distinguished patients with AD from normal control subjects with more than 86% accuracy. Furthermore, most identified episodic memory-related regions showed significantly different amyloid-β positron emission tomography measurements among the AD, MCI, and normal control groups. Moreover, the classification outputs significantly correlated with cognitive assessment scores and cerebrospinal fluid pathological biomarkers' levels in the MCI and AD groups.

CONCLUSIONS

Neuroimaging features can reflect individual episodic memory function and serve as potential diagnostic biomarkers of AD.

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.

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.

Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy

Introduction

Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment.

Methods

In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group.

Results

Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (E_glo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of E_glo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group.

Conclusion

These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.

Inherent regional brain activity changes in male obstructive sleep apnea with mild cognitive impairment: A resting-state magnetic resonance study

Obstructive sleep apnea (OSA) is the most common sleep disorder worldwide. Previous studies have shown that OSA patients are often accompanied by cognitive function loss, and the underlying neurophysiological mechanism is still unclear. This study aimed to determine whether there are differences in regional homogeneity (Reho) and functional connectivity (FC) across the brain between OSA patients with MCI (OSA-MCI) and those without MCI (OSA-nMCI) and whether such differences can be used to distinguish the two groups. Resting state magnetic resonance data were collected from 48 OSA-MCI patients and 47 OSA-nMCI patients. The brain regions with significant differences in Reho and FC between the two groups were identified, and the Reho and FC features were combined with machine learning methods for classification. Compared with OSA-nMCI patients, OSA-MCI patients showed significantly lower Reho in bilateral lingual gyrus and left superior temporal gyrus. OSA-MCI patients also showed significantly lower FC between the bilateral lingual gyrus and bilateral cuneus, left superior temporal gyrus and left middle temporal gyrus, middle frontal gyrus, and bilateral posterior cingulate/calcarine/cerebellar anterior lobe. Based on Reho and FC features, logistic regression classification accuracy was 0.87; sensitivity, 0.70; specificity, 0.89; and area under the curve, 0.85. Correlation analysis showed that MoCA scale score in OSA patients was significant positive correlation sleep efficiency and negatively correlation with neck circumference. In conclusion, our results showed that the OSA-MCI group showed decreased Reho and FC in specific brain regions compared with the OSA-nMCI group, which may help to understand the underlying neuroimaging mechanism of OSA leading to cognitive dysfunction and may serve as a potential biomarker to distinguish whether OSA is accompanied by cognitive impairment.

Quantitative Assessment of Resting-State Functional Connectivity MRI to Differentiate Amnestic Mild Cognitive Impairment, Late-Onset Alzheimer's Disease From Normal Subjects

BACKGROUND

Alzheimer disease (AD) is a neurological disorder with brain network dysfunction. Investigation of the brain network functional connectivity (FC) alterations using resting-state functional MRI (rs-fMRI) can provide valuable information about the brain network pattern in early AD diagnosis.

PURPOSE

To quantitatively assess FC patterns of resting-state brain networks and graph theory metrics (GTMs) to identify potential features for differentiation of amnestic mild cognitive impairment (aMCI) and late-onset AD from normal.

STUDY TYPE

Prospective.

SUBJECTS

A total of 14 normal, 16 aMCI, and 13 late-onset AD.

FIELD STRENGTH/SEQUENCE

A 3.0 T; rs-fMRI: single-shot 2D-EPI and T1-weighted structure: MPRAGE.

ASSESSMENT

By applying bivariate correlation coefficient and Fisher transformation on the time series of predefined ROIs' pairs, correlation coefficient matrixes and ROI-to-ROI connectivity (RRC) were extracted. By thresholding the RRC matrix (with a threshold of 0.15), a graph adjacency matrix was created to compute GTMs.

STATISTICAL TESTS

Region of interest (ROI)-based analysis: parametric multivariable statistical analysis (PMSA) with a false discovery rate using (FDR)-corrected P < 0.05 cluster-level threshold together with posthoc uncorrected P < 0.05 connection-level threshold. Graph-theory analysis (GTA): P-FDR-corrected < 0.05. One-way ANOVA and Chi-square tests were used to compare clinical characteristics.

RESULTS

PMSA differentiated AD from normal, with a significant decrease in FC of default mode, salience, dorsal attention, frontoparietal, language, visual, and cerebellar networks. Furthermore, significant increase in overall FC of visual and language networks was observed in aMCI compared to normal. GTA revealed a significant decrease in global-efficiency (28.05 < 45), local-efficiency (22.98 < 24.05), and betweenness-centrality (14.60 < 17.39) for AD against normal. Moreover, a significant increase in local-efficiency (33.46 > 24.05) and clustering-coefficient (25 > 20.18) were found in aMCI compared to normal.

DATA CONCLUSION

This study demonstrated resting-state FC potential as an indicator to differentiate AD, aMCI, and normal. GTA revealed brain integration and breakdown by providing concise and comprehensible statistics.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

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.

Exploring Network Properties Across Preclinical Stages of Alzheimer’s Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study

Background: Visual short-term memory (VSTMT) and visual attention (VAT) exhibit decline in the Alzheimer’s disease (AD) continuum; however, network disruption in preclinical stages is scarcely explored. Objective: To advance our knowledge about brain networks in AD and discover connectivity alterations during VSTMT and VAT. Methods: Twelve participants with AD, 23 with mild cognitive impairment (MCI), 17 with subjective cognitive decline (SCD), and 21 healthy controls (HC) were examined using a neuropsychological battery at baseline and follow-up (three years). At baseline, the subjects were examined using high density electroencephalography while performing a VSTMT and VAT. For exploring network organization, we constructed weighted undirected networks and examined clustering coefficient, strength, and betweenness centrality from occipito-parietal regions. Results: One-way ANOVA and pair-wise t-test comparisons showed statistically significant differences in HC compared to SCD (t (36) = 2.43, p = 0.026), MCI (t (42) = 2.34, p = 0.024), and AD group (t (31) = 3.58, p = 0.001) in Clustering Coefficient. Also with regards to Strength, higher values for HC compared to SCD (t (36) = 2.45, p = 0.019), MCI (t (42) = 2.41, p = 0.020), and AD group (t (31) = 3.58, p = 0.001) were found. Follow-up neuropsychological assessment revealed converge of 65% of the SCD group to MCI. Moreover, SCD who were converted to MCI showed significant lower values in all network metrics compared to the SCD that remained stable. Conclusion: The present findings reveal that SCD exhibits network disorganization during visual encoding and retrieval with intermediate values between MCI and HC.

Progressive cortical and sub-cortical alterations in patients with anti-N-methyl-D-aspartate receptor encephalitis

BACKGROUND

Advanced structural analyses are increasingly being highly valued to uncover pathophysiological understanding of anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis. Therefore, we aimed to explore whether and how antibody-mediated NMDAR dysfunction affected cortical and sub-cortical brain morphology and their relationship with clinical symptoms.

METHODS

We performed surface-based morphometry analyses, hippocampal segmentation, and correlational analyses in 24 patients with anti-NMDAR encephalitis after acute disease stage and 30 normal controls (NC) in this case-control study.

RESULTS

Patients showed significantly decreased cortical alterations mainly in language network (LN) and default mode network (DMN), as well as decreased gray matter volume in left cornu ammonis 1 (CA1) body of hippocampus. Further correlation analyses showed that the decreased cortical thickness in the right superior frontier gyrus was associated with decreased cognitive scores, the decreased cortical volume in the right pars triangulari and decreased surface area in the right pars operculari were associated with decreased memory scores, whereas decreased gray matter volume in the left CA1 body was significantly correlated with longer time between first symptom and imaging in the patients.

CONCLUSION

These results suggested that cognitive impairments resulted from long-term sequelae of the encephalitis were mainly associated with cortical alterations in LN and DMN and sub-cortical atrophy of left CA1 body, which can be served as effective features to assess disease progression in clinical routine examination.

Systematic Review of Different Neuroimaging Correlates in Mild Cognitive Impairment and Alzheimer's Disease

Alzheimer's disease (AD) is a heterogeneous progressive neurocognitive disorder. Although different neuroimaging modalities have been used for the identification of early diagnostic and prognostic factors of AD, there is no consolidated view of the findings from the literature. Here, we aim to provide a comprehensive account of different neural correlates of cognitive dysfunction via magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI) (resting-state and task-related), positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) modalities across the cognitive groups i.e., normal cognition, mild cognitive impairment (MCI), and AD. A total of 46 meta-analyses met the inclusion criteria, including relevance to MCI, and/or AD along with neuroimaging modality used with quantitative and/or functional data. Volumetric MRI identified early anatomical changes involving transentorhinal cortex, Brodmann area 28, followed by the hippocampus, which differentiated early AD from healthy subjects. A consistent pattern of disruption in the bilateral precuneus along with the medial temporal lobe and limbic system was observed in fMRI, while DTI substantiated the observed atrophic alterations in the corpus callosum among MCI and AD cases. Default mode network hypoconnectivity in bilateral precuneus (PCu)/posterior cingulate cortices (PCC) and hypometabolism/hypoperfusion in inferior parietal lobules and left PCC/PCu was evident. Molecular imaging revealed variable metabolite concentrations in PCC. In conclusion, the use of different neuroimaging modalities together may lead to identification of an early diagnostic and/or prognostic biomarker for AD.

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.

Abnormal Default-Mode Network Homogeneity in Patients With Mild Cognitive Impairment in Chinese Communities

Background and Objective: Current evidence suggests that abnormalities within the default-mode network (DMN) play a key role in the broad-scale cognitive problems that characterize mild cognitive impairment (MCI). However, little is known about the alterations of DMN network homogeneity (NH) in MCI.

Methods: Resting-state functional magnetic resonance imaging scans (rs-fMRI) were collected from 38 MCI patients and 69 healthy controls matched for age, gender, and education. NH approach was employed to analyze the imaging dataset. Cognitive performance was measured with the Chinese version of Alzheimer's disease assessment scale-Cognitive subscale (ADAS-Cog).

Results: Two groups have no significant differences between demographic factors. And mean ADAS-Cog score in MCI was 12.02. MCI patients had significantly lower NH values than controls in the right anterior cingulate cortex and significantly higher NH values in the ventral medial prefrontal cortex(vmPFC) than those in healthy controls. No significant correlations were found between abnormal NH values and ADAS-Cog in the patients.

Conclusions: These findings provide further evidence that abnormal NH of the DMN exists in MCI, and highlight the significance of DMN in the pathophysiology of cognitive problems occurring in MCI.

A study of regional homogeneity of resting-state Functional Magnetic Resonance Imaging in mild cognitive impairment

Mild cognitive impairment (MCI) is considered to be the early stage of Alzheimer's disease (AD), but the diagnostic predictive markers for MCI patients are still unclear. Here we have identified the brain function activity changes in MCI patients by using the resting-state functional magnetic resonance imaging (rs-fMRI). A total of 28 MCI patients and 38 age- and gender-matched healthy controls from the Wuxi Mental Health Center were recruited, and their abnormal spontaneous brain activities in the MCI were examined. The results showed that, compared with the healthy controls, MCI patients exhibited reduced regional homogeneity (ReHo) in the right superior temporal gyrus, right middle temporal gyrus, left angular gyrus and superior marginal gyrus. In addition, the correlation analysis revealed that ReHo in these regions were not correlated with the AD Assessment Scale-Cognitive score in MCI. We concluded abnormalities in the right superior temporal gyrus, right middle temporal gyrus, left angular gyrus and superior marginal gyrus with MCI, suggesting that the right language network may be impaired in MCI, which may provide a better understanding of dementia progression and potentially comprehensive treatment in MCI.

Altered intrinsic brain activity and regional cerebral blood flow in patients with chronic neck and shoulder pain

Purpose

To identify the changes of intrinsic brain activity and regional cerebral blood flow in patients with chronic neck and shoulder pain (CNSP) by using amplitude of low-frequency fluctuation (ALFF) analysis and arterial spin labelling study.

Material and methods

In total, 28 CNSP patients and 25 age-matched and sex-matched healthy controls (HCs) participated in the study. Resting-state functional magnetic resonance imaging (rs-fMRI) and arterial spin labelling (ASL) MRI were acquired. Correlations between ALFF and cerebral blood flow (CBF) were analysed. Subsequently, the differences in ALFF and CBF were compared in the two groups. Finally, the visual analogue scale (VAS) was also assessed in the CNSP group.

Results

Compared with HCs, CNSP patients showed significantly abnormal ALFF and CBF in several brain regions, including the cerebellum posterior lobe, middle orbitofrontal gyrus, medial superior frontal gyrus, middle temporal gyrus, precuneus, cingulate gyrus, middle occipital gyrus, middle frontal gyrus, postcentral gyrus, precentral gyrus, and superior parietal gyrus. Correlation analysis showed that the ALFF value of the medial superior frontal gyrus positively correlated with the VAS score. However, no correlation was found between the CBF values and the VAS score.

Conclusions

The altered ALFF and CBF values in CNSP patients were observed in different pain-related brain regions that were involved in pain modulation and perception. The combination of rs-fMRI and ASL MRI might provide complementary information for increasing our understanding of the neuropathology in CNSP.

Alterations in intra- and internetwork functional connectivity associated with levetiracetam treatment in temporal lobe epilepsy

OBJECTIVE

Levetiracetam (LEV) is an antiepileptic drug with a novel pharmacological mechanism. Advances in functional magnetic resonance imaging (fMRI) enable researchers to explore the cognitive effects of antiepileptic drugs on the living brain. This study aimed to explore how the functional connectivity patterns of the cognitive networks changed in association with LEV treatment.

METHODS

Patients with temporal lobe epilepsy (TLE), including both users and nonusers of LEV, were included in this study along with healthy controls. Core cognitive networks were extracted using an independent component analysis approach. Functional connectivity patterns within and between networks were investigated. The relationships between functional connectivity patterns and clinical characteristics were also examined.

RESULTS

The patterns of intranetwork connectivity in the default mode network (DMN), left executive control network (lECN), and dorsal attention network (DAN) differed among the three groups. The internetwork interactions did not show intergroup differences once corrected for multiple comparisons. No correlation between functional connectivity and clinical characteristics was found in patients with TLE.

CONCLUSIONS

Changes in intranetwork connectivity are a key effect of LEV administration.

SIGNIFICANCE

Alterations in intranetwork connectivity patterns may underlie the cognitive effects of LEV administration; this finding improves our understanding of the neural mechanisms of LEV therapy.

The effect of white matter signal abnormalities on default mode network connectivity in mild cognitive impairment

Regions within the default mode network (DMN) are particularly vulnerable to Alzheimer's disease pathology and mechanisms of DMN disruption in mild cognitive impairment (MCI) are still unclear. White matter lesions are presumed to be mechanistically linked to vascular dysfunction whereas cortical atrophy may be related to neurodegeneration. We examined associations between DMN seed‐based connectivity, white matter lesion load, and cortical atrophy in MCI and cognitively healthy controls. MCI showed decreased functional connectivity (FC) between the precuneus‐seed and bilateral lateral temporal cortex (LTC), medial prefrontal cortex (mPFC), posterior cingulate cortex, and inferior parietal lobe compared to those with controls. When controlling for white matter lesion volume, DMN connectivity differences between groups were diminished within bilateral LTC, although were significantly increased in the mPFC explained by significant regional associations between white matter lesion volume and DMN connectivity only in the MCI group. When controlling for cortical thickness, DMN FC was similarly decreased across both groups. These findings suggest that white matter lesions and cortical atrophy are differentially associated with alterations in FC patterns in MCI. Associations between white matter lesions and DMN connectivity in MCI further support at least a partial but important vascular contribution to age‐associated neural and cognitive impairment.

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

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

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

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

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

A Connectomic Atlas of the Human Cerebrum-Chapter 4: The Medial Frontal Lobe, Anterior Cingulate Gyrus, and Orbitofrontal Cortex

In this supplement, we build on work previously published under the Human Connectome Project. Specifically, we show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In part 4, we specifically address regions relevant to the medial frontal lobe, anterior cingulate gyrus, and orbitofrontal cortex.

A Connectomic Atlas of the Human Cerebrum-Chapter 8: The Posterior Cingulate Cortex, Medial Parietal Lobe, and Parieto-Occipital Sulcus

In this supplement, we build on work previously published under the Human Connectome Project. Specifically, we seek to show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In part 8, we specifically address regions relevant to the posterior cingulate cortex, medial parietal lobe, and the parieto-occipital sulcus.

Recent advances in the use of imaging in psychiatry: functional magnetic resonance imaging of large-scale brain networks in late-life depression

Advances in neuroimaging have identified neural systems that contribute to clinical symptoms that occur across various psychiatric disorders. This transdiagnostic approach to understanding psychiatric illnesses may serve as a precise guide to identifying disease mechanisms and informing successful treatments. While this work is ongoing across multiple psychiatric disorders, in this article we emphasize recent findings pertaining to major depression in the elderly, or late-life depression (LLD), a common and debilitating neuropsychiatric illness. We discuss how neural functioning of three networks is linked to symptom presentation, illness course, and cognitive decline in LLD. These networks are (1) an executive control network responsible for complex cognitive processing, (2) a default mode network normally deactivated during cognitive demanding when individuals are at rest, and a (3) salience network relevant to attending to internal and external emotional and physiological sensations. We discuss how dysfunction in multiple networks contributes to common behavioral syndromes, and we present an overview of the cognitive control, default mode, and salience networks observed in LLD.

Abnormal amplitude of low frequency fluctuation and functional connectivity in non-neuropsychiatric systemic lupus erythematosus: a resting-state fMRI study

PURPOSE

To explore the amplitude of low frequency fluctuation (ALFF) and functional connectivity (FC) disorders in non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) patients by resting-state functional magnetic resonance imaging (rs-fMRI) and to study whether there are some clinical biomarkers that can be used to monitor the brain dysfunction.

METHODS

Based on the rs-fMRI data of 36 non-NPSLE patients and 30 normal controls, we first obtained the regions with abnormal ALFF signals in non-NPSLE patients. Then, by taking these areas as seed regions of interest (ROIs), we calculated the FC between ROIs and the whole brain to assess the network-level alterations. Finally, we correlated the altered values of ALFF and FC in non-NPSLE patients to some clinical data.

RESULTS

Compared with the controls, non-NPSLE patients showed decreased ALFF in bilateral precuneus and increased ALFF in right cuneus and right calcarine fissure surrounding cortex (CAL). At network level, non-NPSLE patients exhibited higher FC between left precuneus and left middle occipital gyrus (MOG)/left superior occipital gyrus (SOG)/right middle frontal gyrus (MFG)/right dorsolateral superior frontal gyrus (SFGdor), and higher FC between right cuneus and bilateral precuneus/left posterior cingulate gyrus (PCG). The abnormal ALFF in right CAL and abnormal FC in right cuneus-left precuneus, right cuneus-right precuneus, and right cuneus-left PCG were correlated with the patients' certain clinical data (p < 0.05).

CONCLUSION

Rs-fMRI is a promising tool for detecting the brain function disorders in non-NPSLE patients and to help understand the neurophysiological mechanisms. C4 and Systemic Lupus Erythematosus Disease Activity Index may be biomarkers of brain dysfunction in non-NPSLE patients.

Alterations of brain local functional connectivity in amnestic mild cognitive impairment

Background

Resting-state functional magnetic resonance imaging studies using a regional homogeneity (ReHo) method have reported that amnestic mild cognitive impairment (aMCI) was associated with abnormalities in local functional connectivity. However, their results were not conclusive.

Methods

Seed-based d Mapping was used to conduct a coordinate-based meta-analysis to identify consistent ReHo alterations in aMCI.

Results

We identified 10 studies with 11 datasets suitable for inclusion, including 378 patients with aMCI and 435 healthy controls. This meta-analysis identified significant ReHo alterations in patients with aMCI relative to healthy controls, mainly within the default mode network (DMN) (bilateral posterior cingulate cortex [PCC], right angular gyrus, bilateral middle temporal gyri, and left parahippocampal gyrus/hippocampus), executive control network (right superior parietal lobule and dorsolateral prefrontal cortex), visual network (right lingual gyrus and left middle occipital gyrus), and sensorimotor network (right paracentral lobule/supplementary motor area, right postcentral gyrus and left posterior insula). Significant heterogeneity of ReHo alterations in the bilateral PCC, left parahippocampal gyrus/hippocampus, and right superior parietal lobule/angular gyrus was observed. Exploratory meta-regression analyses indicated that general cognitive function, gender distribution, age, and education level partially contributed to this heterogeneity.

Conclusions

This study provides provisional evidence that aMCI is associated with abnormal ReHo within the DMN, executive control network, visual network, and sensorimotor network. These local functional connectivity alterations suggest coexistence of functional deficits and compensation in these networks. These findings contribute to the modeling of brain functional connectomes and to a better understanding of the neural substrates of aMCI. Confounding factors merit much attention and warrant future investigations.

Electronic supplementary material

The online version of this article (10.1186/s40035-018-0134-8) contains supplementary material, which is available to authorized users.