Default mode network integrity changes contribute to cognitive deficits in subcortical vascular cognitive impairment, no dementia

Effects of computerized cognitive training on functional brain networks in patients with vascular cognitive impairment and no dementia

AIMS

Previous neuroimaging studies of vascular cognitive impairment, no dementia (VCIND), have reported functional alterations, but far less is known about the effects of cognitive training on functional connectivity (FC) of intrinsic connectivity networks (ICNs) and how they relate to intervention-related cognitive improvement. This study provides comprehensive research on the changes in intra- and inter-brain functional networks in patients with VCIND who received computerized cognitive training, with a focus on the underlying mechanisms and potential therapeutic strategies.

METHODS

We prospectively collected 60 patients with VCIND who were randomly divided into the training group (N = 30) receiving computerized cognitive training and the control group (N = 30) receiving fixed cognitive training. Functional MRI scans and cognitive assessments were performed at baseline, at the 7-week training, and at the 6-month follow-up. Utilizing templates for ICNs, the study employed a linear mixed model to compare intra- and inter-network FC changes between the two groups. Pearson correlation was applied to calculate the relationship between FC and cognitive function.

RESULTS

We found significantly decreased intra-network FC within the default mode network (DMN) following computerized cognitive training at Month 6 (p = 0.034), suggesting a potential loss of functional specialization. Computerized training led to increased functional coupling between the DMN and sensorimotor network (SMN) (p = 0.01) and between the language network (LN) and executive control network (ECN) at Month 6 (p < 0.001), indicating compensatory network adaptations in patients with VCIND. Notably, the intra-LN exhibited enhanced functional specialization after computerized cognitive training (p = 0.049), with significant FC increases among LN regions, which correlated with improvements in neuropsychological measures (p < 0.05), emphasizing the targeted impact of computerized cognitive training on language abilities.

CONCLUSIONS

This study provides insights into neuroplasticity and adaptive changes resulting from cognitive training in patients with VCIND, with implications for potential therapeutic strategies.

Effect of Repetitive Transcranial Magnetic Stimulation on Post-Stroke Comorbid Cognitive Impairment and Depression: A Randomized Controlled Trial

Background

There are currently no uniform treatments for post-stroke comorbid cognitive impairment and depression (PSCCID).

Objective

To verify whether repetitive transcranial magnetic stimulation (rTMS) can improve PSCCID symptoms and explore the underlying roles of resting-state functional magnetic resonance imaging (rs-fMRI).

Methods

Thirty PSCCID patients were randomized in a 1 : 1 ratio to receive 4 weeks of rTMS (intervention group) or sham rTMS (control group) over the left dorsolateral prefrontal cortex (DLPFC). rs-fMRI was acquired to analyze the functional plasticity of brain regions at baseline and immediately after the last intervention.

Results

Cognition, depression status, and neural electrophysiology were improved in both intervention and control groups after treatment (p = 0.015-0.042), and the intervention group had more significant improvement than the control group. Analysis of functional connectivities (FCs) within the default mood network (DMN) showed that the connection strength of the left temporal pole/left parahippocampal cortex and right lateral temporal cortex/right retrosplenial cortex in the intervention group were enhanced compared with its pre-intervention and that in the control group after treatment (p < 0.05), and the both FC values were positively correlated with MMSE scores (p < 0.001). The intervention group had stronger FCs within the DMN compared with the control group after treatment, and some of the enhanced FCs were correlated with the P300 latency and amplitude.

Conclusions

rTMS over the left DLPFC is an effective treatment for improving both cognitive impairment and depression among patients with PSCCID. The enhanced FCs within the DMN may serve as a compensatory functional recombination to promote clinical recovery.

Multimodal magnetic resonance imaging on brain structure and function changes in vascular cognitive impairment without dementia

Vascular cognitive impairment not dementia (VCIND) is one of the three subtypes of vascular cognitive impairment (VCI), with cognitive dysfunction and symptoms ranging between normal cognitive function and vascular dementia. The specific mechanisms underlying VCIND are still not fully understood, and there is a lack of specific diagnostic markers in clinical practice. With the rapid development of magnetic resonance imaging (MRI) technology, structural MRI (sMRI) and functional MRI (fMRI) have become effective methods for exploring the neurobiological mechanisms of VCIND and have made continuous progress. This article provides a comprehensive overview of the research progress in VCIND using multimodal MRI, including sMRI, diffusion tensor imaging, resting-state fMRI, and magnetic resonance spectroscopy. By integrating findings from these multiple modalities, this study presents a novel perspective on the neuropathological mechanisms underlying VCIND. It not only highlights the importance of multimodal MRI in unraveling the complex nature of VCIND but also lays the foundation for future research examining the relationship between brain structure, function, and cognitive impairment in VCIND. These new perspectives and strategies ultimately hold the potential to contribute to the development of more effective diagnostic tools and therapeutic interventions for VCIND.

Functional abnormalities of the cerebellum in vascular mild cognitive impairment

OBJECTIVES

The alterations in cerebellar activity that occur in vascular mild cognitive impairment remain largely unexplored. This study aimed to investigate potential associations between abnormal cerebellar functional connectivity (FC) and changes in cognitive function by examining intracerebellar and cerebellar-cerebral FC.

METHODS

MRI data were collected from seventy-two patients with vascular mild cognitive impairment (VMCI), comprising 38 patients with small vessel mild cognitive impairment (SVMCI) and 34 with poststroke mild cognitive impairment (PSMCI), and from 43 demographically matched healthy controls (HCs). Changes in FC between subregions within the cerebellum and from each cerebellar subregion to the selected cerebral seed points in VMCI patients were calculated, and the association of these changes with cognitive function was examined.

RESULTS

Compared with HCs, we found that VMCI patients had 11 cerebellar subregions showing significant differences (mainly decreases) in FC with brain regions in the default-mode network (DMN), sensory-motor network (SMN), and frontoparietal network (FPN). In the intracerebellar FC analysis, 47 (8%) cerebellar connections had significant intergroup differences, mainly a reduced magnitude of FC in VMCI patients. In the correlation analysis, higher Montreal Cognitive Assessment (MoCA) scores were correlated with stronger intracerebellar FC (left crus II-right lobule VI, left crus II-right lobule VIIb) and cerebellar-cerebral FC (right lobule X-left precuneus, vermal lobule IX-right inferior parietal lobule) in both the SVMCI and PSMCI groups.

CONCLUSION

These findings suggest prominent intracerebellar and cerebellar-cerebral FC abnormalities in VMCI patients, contributing evidence for a possible role of the cerebellum in cognitive processes.

Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease

INTRODUCTION

It is challenging to predict which patients who meet criteria for subcortical ischemic vascular disease (SIVD) will ultimately progress to subcortical vascular cognitive impairment (SVCI).

METHODS

We collected clinical information, neuropsychological assessments, T1 imaging, diffusion tensor imaging, and resting-state functional magnetic resonance imaging from 83 patients with SVCI and 53 age-matched patients with SIVD without cognitive impairment. We built an unsupervised machine learning model to isolate patients with SVCI. The model was validated using multimodal data from an external cohort comprising 45 patients with SVCI and 32 patients with SIVD without cognitive impairment.

RESULTS

The accuracy, sensitivity, and specificity of the unsupervised machine learning model were 86.03%, 79.52%, and 96.23% and 80.52%, 71.11%, and 93.75% for internal and external cohort, respectively.

DISCUSSION

We developed an accurate and accessible clinical tool which requires only data from routine imaging to predict patients at risk of progressing from SIVD to SVCI.

HIGHLIGHTS

Our unsupervised machine learning model provides an accurate and accessible clinical tool to predict patients at risk of progressing from subcortical ischemic vascular disease (SIVD) to subcortical vascular cognitive impairment (SVCI) and requires only data from imaging routinely used during the diagnosis of suspected SVCI. The model yields good accuracy, sensitivity, and specificity and is portable to other cohorts and to clinical practice to distinguish patients with SIVD at risk for progressing to SVCI. The model combines assessment of diffusion tensor imaging and functional magnetic resonance imaging measures in patients with SVCI to analyze whether the "disconnection hypothesis" contributes to functional and structural changes and to the clinical presentation of SVCI.

Frequency-dependent white-matter functional network changes associated with cognitive deficits in subcortical vascular cognitive impairment

Vascular cognitive impairment (VCI) refers to all forms of cognitive decline associated with cerebrovascular diseases, in which white matter (WM) is highly vulnerable. Although previous studies have shown that blood oxygen level-dependent (BOLD) signals inside WM can effectively reflect neural activities, whether WM BOLD signal alterations are present and their roles underlying cognitive impairment in VCI remain largely unknown. In this study, 36 subcortical VCI (SVCI) patients and 36 healthy controls were enrolled to evaluate WM dysfunction. Specifically, fourteen distinct WM networks were identified from resting-state functional MRI using K-means clustering analysis. Subsequently, between-network functional connectivity (FC) and within-network BOLD signal amplitude of WM networks were calculated in three frequency bands (band A: 0.01-0.15 Hz, band B: 0.08-0.15 Hz, and band C: 0.01-0.08 Hz). Patients with SVCI manifested decreased FC mainly in bilateral parietal WM regions, forceps major, superior and inferior longitudinal fasciculi. These connections extensively linked with distinct WM networks and with gray-matter networks such as frontoparietal control, dorsal and ventral attention networks, which exhibited frequency-specific alterations in SVCI. Additionally, extensive amplitude reductions were found in SVCI, showing frequency-dependent properties in parietal, anterior corona radiate, pre/post central, superior and inferior longitudinal fasciculus networks. Furthermore, these decreased FC and amplitudes showed significant positive correlations with cognitive performances in SVCI, and high diagnostic performances for SVCI especially combining all bands. Our study indicated that VCI-related cognitive deficits were characterized by frequency-dependent WM functional abnormalities, which offered novel applicable neuromarkers for VCI.

Frequency-specific alterations in intrinsic low-frequency oscillations in newly diagnosed male patients with obstructive sleep apnea

Purpose

Previous studies found abnormal low-frequency spontaneous brain activity related to cognitive impairment in patients with obstructive sleep apnea (OSA). However, it is unclear if low-frequency spontaneous brain activity is related to specific frequency bands in OSA patients. In this study, we used the amplitude of low-frequency fluctuation (ALFF) method in patients with OSA to explore characteristics of spontaneous brain activity in the classical (0.01–0.1 Hz) and five sub-frequency bands (slow-2 to slow-6) and analyzed the relationship between spontaneous brain activity and clinical evaluation was analyzed.

Patients and methods

Resting-state magnetic resonance imaging data and clinical assessments were collected from 52 newly-diagnosed OSA patients and 62 healthy controls (HCs). We calculated the individual group ALFF values in the classical and five different sub-frequency bands. A two-sample t-test compared ALFF differences, and one-way analysis of variance explored interactions in frequency bands between the two groups.

Results

ALFF values in the OSA group were lower than those in the HC group in the bilateral precuneus/posterior cingulate cortex, bilateral angular gyrus, left inferior parietal lobule, brainstem, and right fusiform gyrus. In contrast, ALFF values in the OSA group were higher than those in the HC group in the bilateral cerebellum posterior lobe, bilateral superior frontal gyrus, bilateral middle frontal gyrus, left inferior frontal gyrus, left inferior temporal gyrus, and left fusiform gyrus. Some ALFF values in altered brain regions were associated with body mass index, apnea-hypopnea index, neck circumference, snoring history, minimum SaO₂, average SaO₂, arousal index, oxygen reduction index, deep sleep period naming, abstraction, and delayed recall in specific frequency bands.

Conclusion

Our results indicated the existence of frequency-specific differences in spontaneous brain activity in OSA patients, which were related to cognitive and other clinical symptoms. This study identified frequency-band characteristics related to brain damage, expanded the cognitive neuroimaging mechanism, and provided additional OSA neuroimaging markers.

Mapping cortical disease-burden at individual-level in frontotemporal dementia: implications for clinical care and pharmacological trials

Imaging studies of FTD typically present group-level statistics between large cohorts of genetically, molecularly or clinically stratified patients. Group-level statistics are indispensable to appraise unifying radiological traits and describe genotype-associated signatures in academic studies. However, in a clinical setting, the primary objective is the meaningful interpretation of imaging data from individual patients to assist diagnostic classification, inform prognosis, and enable the assessment of progressive changes compared to baseline scans. In an attempt to address the pragmatic demands of clinical imaging, a prospective computational neuroimaging study was undertaken in a cohort of patients across the spectrum of FTD phenotypes. Cortical changes were evaluated in a dual pipeline, using standard cortical thickness analyses and an individualised, z-score based approach to characterise subject-level disease burden. Phenotype-specific patterns of cortical atrophy were readily detected with both methodological approaches. Consistent with their clinical profiles, patients with bvFTD exhibited orbitofrontal, cingulate and dorsolateral prefrontal atrophy. Patients with ALS-FTD displayed precentral gyrus involvement, nfvPPA patients showed widespread cortical degeneration including insular and opercular regions and patients with svPPA exhibited relatively focal anterior temporal lobe atrophy. Cortical atrophy patterns were reliably detected in single individuals, and these maps were consistent with the clinical categorisation. Our preliminary data indicate that standard T1-weighted structural data from single patients may be utilised to generate maps of cortical atrophy. While the computational interpretation of single scans is challenging, it offers unrivalled insights compared to visual inspection. The quantitative evaluation of individual MRI data may aid diagnostic classification, clinical decision making, and assessing longitudinal changes.

Functional Connectivity, Physical Activity, and Neurocognitive Performances in Patients with Vascular Cognitive Impairment, No Dementia

BACKGROUND

Vascular Cognitive Impairment, No Dementia (VCIND) is a key stage at which early intervention will delay or prevent dementia. The pathophysiology of VCIND posits that a lesion in a single location in the brain has the ability to disrupt brain networks, and the subsequent abnormal Functional Connectivity (FC) of brain networks leads to deficits in corresponding neurobehavioral domains. In this study, we tested the hypothesis that disrupted anterior cingulate cortex and striatal networks mediated the effects of Physical Activity (PA) on neurobehavioral function.

METHODS

In 27 patients with VCIND, FC within the brain networks and neurobehavioral dysfunction were assessed. The relationship between the cognitive scores, FC, and PA was studied. The Fitbit Charge 2 was used to measure step counts, distance, and calories burned. In patients with VCIND, a cross-sectional Spearman's correlation to analyze the relationship among patient-level measures of PA, cognitive function scores, and FC strength within the brain networks.

RESULTS

Average step counts and average distance were associated with Trail Making Test B (TM-B) time to completion (seconds) and Instrumental Activities of Daily Living (IADL) score (P <0.05). The average calories burned were associated with IADL score (P = 0.009). The FC within the brain networks anchored by left caudal Anterior Cingulate Cortex (ACC) seeds (x= -5, y= 0, z= 36) and (x= -5, y= -10, z= 47) were positively correlated with average step counts and average distance, were negatively correlated with TMB time to completion (seconds), and were positively correlated with IADL score (P < 0.05). The FC within the brain networks anchored by left subgenual ACC seed (x= -5, y= 25, z= -10) were negatively correlated with average step counts and average distance were positively correlated with TMB time to completion (seconds), and were negatively correlated with IADL score (P < 0.05). The FC within the striatal networks was positively correlated with average calories burned and IADL score (P < 0.05).

Amyloid-PET Levels in the Precuneus and Posterior Cingulate Cortices Are Associated with Executive Function Scores in Preclinical Alzheimer's Disease Prior to Overt Global Amyloid Positivity

BACKGROUND

Global amyloid-β (Aβ) deposition in the brain can be quantified by Aβ-PET scans to support or refute a diagnosis of preclinical Alzheimer's disease (pAD). Yet, Aβ-PET scans enable quantitative evaluation of regional Aβ elevations in pAD, potentially allowing even earlier detection of pAD, long before global positivity is achieved. It remains unclear as to whether such regional changes are clinically meaningful.

OBJECTIVE

Test the hypothesis that early focal regional amyloid deposition in the brain is associated with cognitive performance in specific cognitive domain scores in pAD.

METHODS

Global and regional standardized uptake value ratios (SUVr) from 18F-florbetapir PET/CT scanning were determined using the Siemens Syngo.via® Neurology software package across a sample of 99 clinically normal participants with Montreal Cognitive Assessment (MoCA) scores≥23. Relationships between regional SUVr and cognitive test scores were analyzed using linear regression models adjusted for age, sex, and education. Participants were divided into two groups based on SUVr in the posterior cingulate and precuneus gyri (SUVR≥1.17). Between group differences in cognitive test scores were analyzed using ANCOVA models.

RESULTS

Executive function performance was associated with increased regional SUVr in the precuneus and posterior cingulate regions only (p < 0.05). There were no significant associations between memory and Aβ-PET SUVr in any regions of the brain.

CONCLUSION

These data demonstrate that increased Aβ deposition in the precuneus and posterior cingulate (the earliest brain regions affected with Aβ pathology) is associated with changes in executive function that may precede memory decline in pAD.

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.

Disrupted Topological Organization in White Matter Networks in Unilateral Sudden Sensorineural Hearing Loss

Sudden sensorineural hearing loss (SSNHL) is a sudden-onset hearing impairment that rapidly develops within 72 h and is mostly unilateral. Only a few patients can be identified with a defined cause by routine clinical examinations. Recently, some studies have shown that unilateral SSNHL is associated with alterations in the central nervous system. However, little is known about the topological organization of white matter (WM) networks in unilateral SSNHL patients in the acute phase. In this study, 145 patients with SSNHL and 91 age-, gender-, and education-matched healthy controls were evaluated using diffusion tensor imaging (DTI) and graph theoretical approaches. The topological properties of WM networks, including global and nodal parameters, were investigated. At the global level, SSNHL patients displayed decreased clustering coefficient, local efficiency, global efficiency, normalized clustering coefficient, normalized characteristic path length, and small-worldness and increased characteristic path length (p < 0.05) compared with healthy controls. At the nodal level, altered nodal centralities in brain regions involved the auditory network, visual network, attention network, default mode network (DMN), sensorimotor network, and subcortical network (p < 0.05, Bonferroni corrected). These findings indicate a shift of the WM network topology in SSNHL patients toward randomization, which is characterized by decreased global network integration and segregation and is reflected by decreased global connectivity and altered nodal centralities. This study could help us understand the potential pathophysiology of unilateral SSNHL.

Cortical and Subcortical Grey Matter Abnormalities in White Matter Hyperintensities and Subsequent Cognitive Impairment

Grey matter (GM) alterations may contribute to cognitive decline in individuals with white matter hyperintensities (WMH) but no consensus has yet emerged. Here, we investigated cortical thickness and grey matter volume in 23 WMH patients with mild cognitive impairment (WMH-MCI), 43 WMH patients without cognitive impairment, and 55 healthy controls. Both WMH groups showed GM atrophy in the bilateral thalamus, fronto-insular cortices, and several parietal-temporal regions, and the WMH-MCI group showed more extensive and severe GM atrophy. The GM atrophy in the thalamus and fronto-insular cortices was associated with cognitive decline in the WMH-MCI patients and may mediate the relationship between WMH and cognition in WMH patients. Furthermore, the main results were well replicated in an independent dataset from the Alzheimer's Disease Neuroimaging Initiative database and in other control analyses. These comprehensive results provide robust evidence of specific GM alterations underlying WMH and subsequent cognitive impairment.

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.