Longitudinal Alteration of Intrinsic Brain Activity in the Striatum in Mild Cognitive Impairment

Total sleep deprivation alters spontaneous brain activity in medical staff during routine clinical work: a resting-state functional MR imaging study

Objectives

To assess the effect of total sleep deprivation (TSD) on spontaneous brain activity in medical staff during routine clinical practice.

Methods

A total of 36 medical staff members underwent resting-state functional MRI (rs-fMRI) scans and neuropsychological tests twice, corresponding to rested wakefulness (RW) after normal sleep and 24 h of acute TSD. The rs-fMRI features, including the mean fractional amplitude of low-frequency fluctuation (mfALFF), z-score transformed regional homogeneity (zReHo), and functional connectivity (zFC), were compared between RW and TSD. Correlation coefficients between the change in altered rs-fMRI features and the change in altered scores of neuropsychological tests after TSD were calculated. Receiver operating characteristic (ROC) and logistic regression analyses were performed to evaluate the diagnostic efficacy of significantly altered rs-fMRI features in distinguishing between RW and TSD states.

Results

Brain regions, including right superior temporal gyrus, bilateral postcentral gyrus, left medial superior frontal gyrus, left middle temporal gyrus, right precentral gyrus, and left precuneus, showed significantly enhanced rs-fMRI features (mfALFF, zReHo, zFC) after TSD. Moreover, the changes in altered rs-fMRI features of the right superior temporal gyrus, bilateral postcentral gyrus, left middle temporal gyrus, and left precuneus were significantly correlated with the changes in several altered scores of neuropsychological tests. The combination of mfALFF (bilateral postcentral gyrus) and zFC (left medial superior frontal gyrus and left precuneus) showed the highest area under the curve (0.870) in distinguishing RW from TSD.

Conclusion

Spontaneous brain activity alterations occurred after TSD in routine clinical practice, which might explain the reduced performances of these participants in neurocognitive tests after TSD. These alterations might be potential imaging biomarkers for assessing the impact of TSD and distinguishing between RW and TSD states.

White matter alterations in mild cognitive impairment revealed by meta-analysis of diffusion tensor imaging using tract-based spatial statistics

The neuropathological mechanism of mild cognitive impairment (MCI) remains unclarified. Diffusion tensor imaging (DTI) studies revealed white matter (WM) microarchitecture alterations in MCI, but consistent findings and conclusions have not yet been drawn. The present coordinate-based meta-analysis (CBMA) of tract-based spatial statistics (TBSS) studies aimed to identify the most prominent and robust WM abnormalities in patients with MCI. A systematic search of relevant studies was conducted through January 2022 to identify TBSS studies comparing fractional anisotropy (FA) between MCI patients and healthy controls (HC). We used the seed-based d mapping (SDM) software to achieve the CBMA and analyze regional FA alterations in MCI. Meta-regression analysis was subsequently applied to explore the potential associations between clinical variables and FA changes. MCI patients demonstrated significantly decreased FA in widely distributed areas in the corpus callosum (CC), including the genu, body, and splenium of the CC, as well as one cluster in the left striatum. FA in the body of the CC and in three clusters in the splenium of the CC was negatively associated with the mean age. Additionally, FA in the genu of the CC and in three clusters in the splenium of the CC had negative correlations with the MMSE scores. Disrupted integrities of the CC and left striatum might play vital roles in the process of cognitive decline. These findings enhanced our understanding of the neural mechanism underlying WM neurodegeneration in MCI and provided perspectives for the early detection and intervention of dementia.Registration number: CRD42022235716.

Enhanced putamen functional connectivity underlies altered risky decision-making in age-related cognitive decline

Risky decision-making is critical to survival and development, which has been compromised in elderly populations. However, the neural substrates of altered financial risk-taking behavior in aging are still under-investigated. Here we examined the intrinsic putamen network in modulating risk-taking behaviors of Balloon Analogue Risk Task in healthy young and older adults using resting-state fMRI. Compared with the young group, the elderly group showed significantly different task performance. Based on the task performance, older adults were further subdivided into two subgroups, showing young-like and over-conservative risk behaviors, regardless of cognitive decline. Compared with young adults, the intrinsic pattern of putamen connectivity was significantly different in over-conservative older adults, but not in young-like older adults. Notably, age-effects on risk behaviors were mediated via the putamen functional connectivity. In addition, the putamen gray matter volume showed significantly different relationships with risk behaviors and functional connectivity in over-conservative older adults. Our findings suggest that reward-based risky behaviors might be a sensitive indicator of brain aging, highlighting the critical role of the putamen network in maintaining optimal risky decision-making in age-related cognitive decline.

Cognitive decline is associated with frequency-specific resting state functional changes in normal aging

Resting state low-frequency brain activity may aid in our understanding of the mechanisms of aging-related cognitive decline. Our purpose was to explore the characteristics of the amplitude of low-frequency fluctuations (ALFF) in different frequency bands of fMRI to better understand cognitive aging. Thirty-seven cognitively normal older individuals underwent a battery of neuropsychological tests and MRI scans at baseline and four years later. ALFF from five different frequency bands (typical band, slow-5, slow-4, slow-3, and slow-2) were calculated and analyzed. A two-way ANOVA was used to explore the interaction effects in voxel-wise whole brain ALFF of the time and frequency bands. Paired-sample t-test was used to explore within-group changes over four years. Partial correlation analysis was performed to assess associations between the altered ALFF and cognitive function. Significant interaction effects of time × frequency were distributed over inferior frontal gyrus, superior frontal gyrus, right rolandic operculum, left thalamus, and right putamen. Significant ALFF reductions in all five frequency bands were mainly found in the right hemisphere and the posterior cerebellum; whereas localization of the significantly increased ALFF were mainly found in the cerebellum at typical band, slow-5 and slow-4 bands, and left hemisphere and the cerebellum at slow-3, slow-2 bands. In addition, ALFF changes showed frequency-specific correlations with changes in cognition. These results suggest that changes of local brain activity in cognitively normal aging should be investigated in multiple frequency bands. The association between ALFF changes and cognitive function can potentially aid better understanding of the mechanisms underlying normal cognitive aging.

Efficacy and Mechanism of Moxibustion Treatment on Mild Cognitive Impairment Patients: An fMRI Study Using ALFF

Background

Mild Cognitive Impairment (MCI), as a high risk of Alzheimer’s disease (AD), represents a state of cognitive function between normal aging and dementia. Moxibustion may effectively delay the progression of AD, while there is a lack of studies on the treatments in MCI. This study aimed to evaluate the effect of moxibustion treatment revealed by the amplitude of low-frequency fluctuation (ALFF) in MCI.

Method

We enrolled 30 MCI patients and 30 matched healthy controls (HCs) in this study. We used ALFF to compare the difference between MCI and HCs at baseline and the regulation of spontaneous neural activity in MCI patients by moxibustion. The Mini-Mental State Examination and Montreal Cognitive Assessment scores were used to evaluate cognitive function.

Results

Compared with HCs, the ALFF values significantly decreased in the right temporal poles: middle temporal gyrus (TPOmid), right inferior temporal gyrus, left middle cingulate gyrus, and increased in the left hippocampus, left middle temporal gyrus, right lingual gyrus, and right middle occipital gyrus in MCI patients. After moxibustion treatment, the ALFF values notably increased in the left precuneus, left thalamus, right temporal poles: middle temporal gyrus, right middle frontal gyrus, right inferior temporal gyrus, right putamen, right hippocampus, and right fusiform gyrus, while decreased in the bilateral lingual gyrus in MCI patients. The Mini-Mental State Examination and Montreal Cognitive Assessment scores increased after moxibustion treatment, and the increase in Mini-Mental State Examination score was positively correlated with the increase of ALFF value in the right TPOmid, the right insula, and the left superior temporal gyrus.

Conclusion

Moxibustion treatment might improve the cognitive function of MCI patients by modulating the brain activities within the default mode network, visual network, and subcortical network with a trend of increased ALFF values and functional asymmetry of the hippocampus. These results indicate that moxibustion holds great potential in the treatment of MCI.

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).

Multi-Order Brain Functional Connectivity Network-Based Machine Learning Method for Recognition of Delayed Neurocognitive Recovery in Older Adults Undergoing Non-cardiac Surgery

Objectives: Delayed neurocognitive recovery (DNR) seriously affects the post-operative recovery of elderly surgical patients, but there is still a lack of effective methods to recognize high-risk patients with DNR. This study proposed a machine learning method based on a multi-order brain functional connectivity (FC) network to recognize DNR.

Method: Seventy-four patients who completed assessments were included in this study, in which 16/74 (21.6%) had DNR following surgery. Based on resting-state functional magnetic resonance imaging (rs-fMRI), we first constructed low-order FC networks of 90 brain regions by calculating the correlation of brain region signal changing in the time dimension. Then, we established high-order FC networks by calculating correlations among each pair of brain regions. Afterward, we built sparse representation-based machine learning model to recognize DNR on the extracted multi-order FC network features. Finally, an independent testing was conducted to validate the established recognition model.

Results: Three hundred ninety features of FC networks were finally extracted to identify DNR. After performing the independent-sample T test between these features and the categories, 15 features showed statistical differences (P < 0.05) and 3 features had significant statistical differences (P < 0.01). By comparing DNR and non-DNR patients’ brain region connection matrices, it is found that there are more connections among brain regions in DNR patients than in non-DNR patients. For the machine learning recognition model based on multi-feature combination, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the classifier reached 95.61, 92.00, 66.67, and 100.00%, respectively.

Conclusion: This study not only reveals the significance of preoperative rs-fMRI in recognizing post-operative DNR in elderly patients but also establishes a promising machine learning method to recognize DNR.

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.

Altered Spontaneous Brain Activity in Subjects With Different Cognitive States of Biologically Defined Alzheimer's Disease: A Surface-Based Functional Brain Imaging Study

Background: Before the apparent cognitive decline, subjects on the course of Alzheimer's disease (AD) can have significantly altered spontaneous brain activity, which could be potentially used for early diagnosis. As previous studies investigating local brain activity may suffer from the problem of cortical signal aliasing during volume-based analysis, we aimed to investigate the cortical functional alterations in the AD continuum using a surface-based approach. Methods: Based on biomarker profile "A/T," we included 11 healthy controls (HC, A-T-), 22 preclinical AD (CU, A+T+), 33 prodromal AD (MCI, A+T+), and 20 AD with dementia (d-AD, A+T+) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The amplitude of low-frequency fluctuation (ALFF) method was used to evaluate the changes of spontaneous brain activity, which was performed in the classic frequency band (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) band, and slow-5 (0.01-0.027 Hz) band. Results: Under classic frequency band and slow-4 band, analysis of covariance (ANCOVA) showed that there were significant differences of standardized ALFF (zALFF) in the left posterior cingulate cortex (PCC) among the four groups. The post-hoc analyses showed that under the classic frequency band, the AD group had significantly decreased zALFF compared with the other three groups, and the cognitively unimpaired (CU) group had decreased zALFF compared with the healthy control (HC) group. Under the slow-4 band, more group differences were detected (HC > CU/MCI > d-AD). The accuracy of classifying CU, mild cognitive impairment (MCI), and AD from HC by left PCC activity under the slow-4 band were 0.774, 0.744, and 0.920, respectively. Moreover, the zALFF values of the left PCC had significant correlations with cerebrospinal fluid (CSF) biomarkers and neuropsychological tests. Conclusions: Spontaneous brain activity in the left PCC may decrease in preclinical AD when cognitive functions were relatively normal. The combination of a surfaced-based approach and specific frequency band analysis may increase sensitivity for the identification of preclinical AD subjects.

Altered corticostriatal synchronization associated with compulsive-like behavior in APP/PS1 mice

Mild behavioral impairment (MBI), which can include compulsive behavior, is an early sign of Alzheimer's disease (AD), but its underlying neural mechanisms remain unclear. Here, we show that 3-5-month-old APP/PS1 mice display obsessive-compulsive disorder (OCD)-like behavior. The number of parvalbumin-positive (PV) interneurons and level of high gamma (γ_high) oscillation are significantly decreased in the striatum of AD mice. This is accompanied by enhanced β-γ_high coupling and firing rates of putative striatal projection neurons (SPNs), indicating decorrelation between PV interneurons and SPNs. Local field potentials (LFPs) simultaneously recorded in prefrontal cortex (PFC) and striatum (Str) demonstrate a decrease in γ_high-band coherent activity and spike-field coherence in corticostriatal circuits of APP/PS1 mice. Furthermore, levels of GABA_B receptor (GABA_BR), but not GABA_A receptor (GABA_AR), and glutamatergic receptors, were markedly reduced, in line with presymptomatic AD-related behavioral changes. These findings suggest that MBI occurs as early as 3-5 months in APP/PS1 mice and that altered corticostriatal synchronization may play a role in mediating the behavioral phenotypes observed.

DREAM : A Toolbox to Decode Rhythms of the Brain System

Rhythms of the brain are generated by neural oscillations across multiple frequencies. These oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. In practice, the number and ranges of decodable frequency intervals are determined by sampling parameters, often ignored by researchers. To improve the situation, we report on an open toolbox with a graphical user interface for decoding rhythms of the brain system (DREAM). We provide worked examples of DREAM to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM decoded the head motion oscillations and uncovered that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age of 7 to 9 years. It is interesting that the higher frequency bands contain more head movements, and showed stronger age-motion associations but weaker sex-motion interactions. Using data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. The resting-state brain ranks its spontaneous oscillation's amplitudes spatially from high in ventral-temporal areas to low in ventral-occipital areas when the frequency band increased from low to high, while those in part of parietal and ventral frontal regions are reversed. The higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, DREAM adds a reliable and valid tool to mapping human brain function from a multiple-frequency window into brain waves.

Changes of Regional Neural Activity Homogeneity in Preclinical Alzheimer's Disease: Compensation and Dysfunction

INTRODUCTION

Subjective cognitive decline (SCD) is the preclinical stage of Alzheimer's disease and may develop into amnestic mild cognitive impairment (aMCI). Finding suitable biomarkers is the key to accurately identifying SCD. Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies on SCD patients showed functional connectivity disorders. Our goal was to explore whether local neurological homogeneity changes in SCD patients, the relationship between these changes and cognitive function, and similarities of neurological homogeneity changes between SCD and aMCI patients.

MATERIALS AND METHODS

37 cases of the healthy control (HC) group, 39 cases of the SCD group, and 28 cases of the aMCI group were included. Participants underwent rs-fMRI examination and a set of neuropsychological test batteries. Regional homogeneity (ReHo) was calculated and compared between groups. ReHo values were extracted from meaningful regions in the SCD group, and the correlation between ReHo values with the performance of neuropsychological tests was analyzed.

RESULTS

Our results showed significant changes in the ReHo among groups. In the SCD group compared with the HC group, part of the parietal lobe, frontal lobe, and occipital lobe showed decreased ReHo, and the temporal lobe, part of the parietal lobe and the frontal lobe showed increased ReHo. The increased area of ReHo was negatively correlated with the decreased area, and was related to decrease on multiple neuropsychological tests performance. Simultaneously, the changed areas of ReHo in SCD patients are similar to aMCI patients, while aMCI group's neuropsychological test performance was significantly lower than that of the SCD group.

CONCLUSION

There are significant changes in local neurological homogeneity in SCD patients, and related to the decline of cognitive function. The increase of neurological homogeneity in the temporal lobe and adjacent area is negatively correlated with cognitive function, reflecting compensation for local neural damage. These changes in local neurological homogeneity in SCD patients are similar to aMCI patients, suggesting similar neuropathy in these two stages. However, the aMCI group's cognitive function was significantly worse than that of the SCD group, suggesting that this compensation is limited. In summary, regional neural activity homogeneity may be a potential biomarker for identifying SCD and measuring the disease severity.

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.

Suppressed prefrontal cortex oscillations associate with clinical pain in fibrodysplasia ossificans progressiva

Background

Pain is a highly prevalent symptom experienced by patients across numerous rare musculoskeletal conditions. Much remains unknown regarding the central, neurobiological processes associated with clinical pain in musculoskeletal disease states. Fibrodysplasia ossificans progressiva (FOP) is an inherited condition characterized by substantial physical disability and pain. FOP arises from mutations of the bone morphogenetic protein (BMP) receptor Activin A receptor type 1 (ACVR1) causing patients to undergo painful flare-ups as well as heterotopic ossification (HO) of skeletal muscles, tendons, ligaments, and fascia. To date, the neurobiological processes that underlie pain in FOP have rarely been investigated. We examined pain and central pain mechanism in FOP as a model primary musculoskeletal condition. Central nervous system (CNS) functional properties were investigated in FOP patients (N = 17) stratified into low (0–3; 0–10 Scale) and high (≥ 4) pain cohorts using functional near-infrared spectroscopy (fNIRS). Associations among clinical pain, mental health, and physical health were also quantified using responses derived from a battery of clinical questionnaires.

Results

Resting-state fNIRS revealed suppressed power of hemodynamic activity within the slow-5 frequency sub-band (0.01–0.027 Hz) in the prefrontal cortex in high pain FOP patients, where reduced power of slow-5, prefrontal cortex oscillations exhibited robust negative correlations with pain levels. Higher clinical pain intensities were also associated with higher magnitudes of depressive symptoms.

Conclusions

Our findings not only demonstrate a robust coupling among prefrontal cortex functionality and clinical pain in FOP but lays the groundwork for utilizing fNIRS to objectively monitor and central pain mechanisms in FOP and other musculoskeletal disorders.

The effects of Alzheimer's disease related striatal pathologic changes on the fractional amplitude of low-frequency fluctuations

This paper aims to correlate Alzheimer's disease (AD) related striatal pathologic changes with the fractional amplitude of low-frequency fluctuations (fALLF) in the blood oxygenation level-dependent (BOLD) signal in the resting state functional Magnetic Resonance Imaging (rs-fMRI). A dopamine modulated Izikhevich neuron model based network of striatum region is constructed. Balloon-Windkessel hemodynamic model is used to obtain BOLD signals. fALFF differences between two frequency bands (slow-5:0.01-0.027 Hz; slow-4:0.027-0.073 Hz) are investigated in the case of dopamine depletion, decrease in the synaptic connectivity and the input from cortical and thalamic region, assumed that they are the degenerations occurring in AD.

Immediate Abnormal Intrinsic Brain Activity Patterns in Patients with End-stage Renal Disease During a Single Dialysis Session : Resting-state Functional MRI Study

PURPOSE

To investigate cerebral amplitude of low-frequency fluctuations (ALFF) changes during a single hemodialysis (HD) in end-stage renal disease (ESRD) patients who need maintenance HD.

MATERIALS AND METHODS

A total of 24 patients and 27 healthy subjects were included. The patients underwent neuropsychological tests and took twice resting-state fMRI (rs-fMRI) (before and after HD). Healthy group had one rs-fMRI. The zALFF based on rs-fMRI was calculated. Paired t and independent t test was applied to compare zALFF among groups. The associations between zALFF and duration of HD, ultrafiltration volume, and neuropsychological tests was calculated by partial correlation.

RESULTS

Compared to healthy group, patients before HD showed significant worse performances on digit symbol test (DST) and serial dotting test (SDT). Patients after HD performed DST better than before HD. The patients after HD showed higher zALFF in left putamen than before HD. Multiple regions of both HD groups showed significant lower zALFF than healthy group. The zALFF of left putamen of patients after HD was significant negative correlated with the ultrafiltration volume (R = -0.679). The zALFF in patients before HD exhibited significantly positive or negative correlations with DST and SDT in multiple regions. The zALFF of patients after HD significantly negative correlated with DST in right temporal, positive and negative correlated with ultrafiltration volume in right frontal, left putamen respectively.

CONCLUSION

ESRD patients showed changed spontaneous brain activity and cognitive impairments. After a single HD session, patients performed better in neuropsychological test, and spontaneous brain activity changed in left putamen. Ultrafiltration volume might be associated with activity of left putamen.

Preoperative Altered Spontaneous Brain Activity and Functional Connectivity Were Independent Risk Factors for Delayed Neurocognitive Recovery in Older Adults Undergoing Noncardiac Surgery

Objectives

Recently, it has been demonstrated that patients with subtle preexisting cognitive impairment were susceptible to delayed neurocognitive recovery (DNR). This present study investigated whether preoperative alterations in gray matter volume, spontaneous activity, or functional connectivity (FC) were associated with DNR.

Methods

This was a nested case-control study of older adults (≥60 years) undergoing noncardiac surgery. All patients received MRI scan at least 1 day prior to surgery. Cognitive function was assessed prior to surgery and at 7-14 days postsurgery. Preoperative gray matter volume, amplitude of low-frequency fluctuation (ALFF), and FC were compared between the DNR patients and non-DNR patients. The independent risk factors associated with DNR were identified using a multivariate logistic regression model.

Results

Of the 74 patients who completed assessments, 16/74 (21.6%) had DNR following surgery. There were no differences in gray matter volume between the two groups. However, the DNR patients exhibited higher preoperative ALFF in the bilateral middle cingulate cortex (MCC) and left fusiform gyrus and lower preoperative FC between the bilateral MCC and left calcarine than the non-DNR patients. The multivariate logistic regression analysis showed that higher preoperative spontaneous activity in the bilateral MCC was independently associated with a higher risk of DNR (OR = 3.11, 95% CI, 1.30-7.45; P = 0.011). A longer education duration (OR = 0.57, 95% CI, 0.41-0.81; P = 0.001) and higher preoperative FC between the bilateral MCC and left calcarine (OR = 0.40, 95% CI, 0.18-0.92; P = 0.031) were independently correlated with a lower risk of DNR.

Conclusions

Preoperative higher ALFF in the bilateral MCC and lower FC between the bilateral MCC and left calcarine were independently associated with the occurrence of DNR. The present fMRI study identified possible preoperative neuroimaging risk factors for DNR. This trial is registered with Chinese Clinical Trial Registry ChiCTR-DCD-15006096.

Longitudinal Functional Brain Mapping in Supernormals

Prevention of age-related cognitive decline is an increasingly important topic. Recently, increased attention is being directed at understanding biological models of successful cognitive aging. Here, we examined resting-state brain regional low-frequency oscillations using functional magnetic resonance imaging in 19 older adults with excellent cognitive abilities (Supernormals), 28 older adults with normative cognition, 57 older adults with amnestic mild cognitive impairment, and 26 with Alzheimer's disease. We identified a "Supernormal map", a set of regions whose oscillations were resistant to the aging-associated neurodegenerative process, including the right fusiform gyrus, right middle frontal gyrus, right anterior cingulate cortex, left middle temporal gyrus, left precentral gyrus, and left orbitofrontal cortex. The map was unique to the Supernormals, differentiated this group from cognitive average-ager comparisons, and predicted a 1-year change in global cognition (indexed by the Montreal Cognitive Assessment scores, adjusted R2 = 0.68). The map was also correlated to Alzheimer's pathophysiological features (beta-amyloid/pTau ratio, adjusted R2 = 0.66) in participants with and without cognitive impairment. These findings in phenotypically successful cognitive agers suggest a divergent pattern of brain regions that may either reflect inherent neural integrity that contributes to Supernormals' cognitive success, or alternatively indicate adaptive reorganization to the demands of aging.

Alterations of regional homogeneity in Parkinson's disease with mild cognitive impairment: a preliminary resting-state fMRI study

PURPOSE

Mild cognitive impairment (MCI) is commonly observed in Parkinson's disease (PD), even in the early stages. However, the neural substrates of cognitive impairment in PD remain unclear. The aim of the current study was to investigate the change of local brain function in PD patients with MCI.

METHODS

Fifty patients with PD, including 25 PD patients with MCI (PD-MCI) and 25 PD patients with normal cognition (PD-NC), and 25 age- and sex-matched healthy controls (HC) were enrolled. Conventional magnetic resonance imaging (MRI), 3D structural images, and resting state-functional MRI (rs-fMRI) were performed in all subjects. Regional homogeneity (ReHo) was measured based on the rs-fMRI images to investigate the altered local brain functions.

RESULTS

Brain regions with decreased ReHo were located in the left posterior cerebellar lobe in PD sub-groups compared to the HC group, and the brain regions with increased ReHo were located in the limbic lobe (right precuneus/bilateral middle cingulate cortex) in PD-MCI compared with HC group. PD-MCI presented with increased ReHo in the bilateral precuneus/left superior parietal lobe and decreased ReHo in the left insula compared to PD-NC. ReHo values for the left precuneus were negatively related to neuropsychological scores, and ReHo values for the left insula were positively related to neuropsychological scores in PD subjects.

CONCLUSION

The present study demonstrated abnormal spontaneous synchrony in the left insula and left precuneus in patients with PD-MCI compared to PD-NC, which might provide a novel insight into the diagnosis and clinical treatment of cognitive impairment in PD.

Relationship between changes in resting-state spontaneous brain activity and cognitive impairment in patients with CADASIL

Background

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) mainly manifests with cognitive impairment. Cognitive deficits in patients with CADASIL are correlated with structural brain changes such as lacunar lesion burden, normalized brain volume, and anterior thalamic radiation lesions, but changes in resting-state functional brain activity in patients with CADASIL have not been reported.

Methods

This study used resting-state functional magnetic resonance imaging (fMRI) to measure the amplitude of low-frequency fluctuation (ALFF) in 22 patients with CADASIL and 44 healthy matched controls. A seed-based functional connectivity (FC) analysis was used to investigate whether the dysfunctional areas identified by ALFF analysis exhibited abnormal FC with other brain areas. Pearson’s correlation analysis was used to detect correlations between the ALFF z-score of abnormal brain areas and clinical scores in patients with CADASIL.

Results

Patients with CADASIL exhibited significantly lower ALFF values in the right precuneus and cuneus (Pcu/CU) and higher ALFF values in the bilateral superior frontal gyrus (SFG) and left cerebellar anterior and posterior lobes compared with controls. Patients with CADASIL showed weaker FC between the areas with abnormal ALFF (using peaks in the left and right SFG and the right Pcu/CU) and other brain areas. Importantly, the ALFF z-scores for the left and right SFG were negatively associated with cognitive performance, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment scores (MoCA), respectively, whereas those of the right Pcu/CU were positively correlated with the MMSE score.

Conclusions

This preliminary study provides evidence for changes in ALFF of the right Pcu/CU, bilateral SFG and left cerebellar anterior and posterior lobes, and associations between ALFF values for abnormal brain areas and cognitive performance in patients with CADASIL. Therefore, spontaneous brain activity may be a novel imaging biomarker of cognitive impairment in this population.

Identify a shared neural circuit linking multiple neuropsychiatric symptoms with Alzheimer's pathology

Neuropsychiatric symptoms (NPS) are common in Alzheimer's disease (AD)-associated neurodegeneration. However, NPS lack a consistent relationship with AD pathology. It is unknown whether any common neural circuits can link these clinically disparate while mechanistically similar features with AD pathology. Here, we explored the neural circuits of NPS in AD-associated neurodegeneration using multivariate pattern analysis (MVPA) of resting-state functional MRI data. Data from 98 subjects (70 amnestic mild cognitive impairment and 28 AD subjects) were obtained. The top 10 regions differentiating symptom presence across NPS were identified, which were mostly the fronto-limbic regions (medial prefrontal cortex, caudate, etc.). These 10 regions' functional connectivity classified symptomatic subjects across individual NPS at 69.46-81.27%, and predicted multiple NPS (indexed by Neuropsychiatric Symptom Questionnaire-Inventory) and AD pathology (indexed by baseline and change of beta-amyloid/pTau ratio) all above 70%. Our findings suggest a fronto-limbic dominated neural circuit that links multiple NPS and AD pathology. With further examination of the structural and pathological changes within the circuit, the circuit may shed light on linking behavioral disturbances with AD-associated neurodegeneration.

Amyloid beta-positive subjects exhibit longitudinal network-specific reductions in spontaneous brain activity

Amyloid beta (Aβ) deposition and cognitive decline are key features of Alzheimer's disease. The relationship between Aβ status and changes in neuronal function over time, however, remains unclear. We evaluated the effect of baseline Aβ status on reference region spontaneous brain activity (SBA-rr) using resting-state functional magnetic resonance imaging and fluorodeoxyglucose positron emission tomography in patients with mild cognitive impairment. Patients (N = 62, [43 Aβ-positive]) from the Alzheimer's Disease Neuroimaging Initiative were divided into Aβ-positive and Aβ-negative groups via prespecified cerebrospinal fluid Aβ42 or 18F-florbetapir positron emission tomography standardized uptake value ratio cutoffs measured at baseline. We analyzed interaction of biomarker-confirmed Aβ status with SBA-rr change over a 2-year period using mixed-effects modeling. SBA-rr differences between Aβ-positive and Aβ-negative subjects increased significantly over time within subsystems of the default and visual networks. Changes exhibit an interaction with memory performance over time but were independent of glucose metabolism. Results reinforce the value of resting-state functional magnetic resonance imaging in evaluating Alzheimer''s disease progression and suggest spontaneous neuronal activity changes are concomitant with cognitive decline.

Neurofilament relates to white matter microstructure in older adults

Cerebrospinal fluid (CSF) neurofilament light (NFL) is a protein biomarker of axonal injury. To study whether NFL is associated with diffusion tensor imaging (DTI) measurements of white matter (WM) microstructure, Vanderbilt Memory & Aging Project participants with normal cognition (n = 77), early mild cognitive impairment (n = 15), and MCI (n = 55) underwent lumbar puncture to obtain CSF and 3T brain MRI. Voxel-wise analyses cross-sectionally related NFL to DTI metrics, adjusting for demographic and vascular risk factors. Increased NFL correlated with multiple DTI metrics (p-values < 0.05). An NFL × diagnosis interaction (excluding early mild cognitive impairment) on WM microstructure (p-values < 0.05) was detected, with associations strongest among MCI. Multiple NFL × CSF biomarker interactions were detected. Associations between NFL and worse WM metrics were strongest among amyloid-β42-negative, tau-positive, and suspected nonamyloid pathology participants. Findings suggest increased NFL, a biomarker of axonal injury, is correlated with compromised WM microstructure. Results highlight the role of elevated NFL in predicting WM damage in cognitively impaired older adults who are amyloid-negative, tau-positive, or meet suspected nonamyloid pathology criteria.

A longitudinal model for functional connectivity networks using resting-state fMRI

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex.

Acute Affective Reactivity and Quality of Life in Older Adults with Amnestic Mild Cognitive Impairment: A Functional MRI Study

OBJECTIVES

Poor quality of life (QoL) is a major concern among older adults with amnestic mild cognitive impairment (MCI). Maladaptive affective regulation and its relevant frontal dysfunction that are often observed in older adults with MCI may provide an insight into the understanding of their QoL.

METHODS

In this case-controlled study, participants (MCI patients, N = 18; healthy comparisons [HC], N = 21) completed cognitive tasks, and underwent resting-state functional magnetic resonance imaging (rs-fMRI) immediately before and after the tasks. The amplitude of low-frequency fluctuations (ALFF) of rs-fMRI signals was calculated to examine the brain's spontaneous activity. The change in valence from the Self-Assessment Manikin indexed affective reactivity. QoL was assessed using Quality of Life-AD measure. Multiple mediator model was used to examine the mediating effect of frontal regions' ALFF reactivity between the affective reactivity and QoL.

RESULTS

The MCI group had significantly worse QoL and more negative affective reactivity than HC group. Less negative affective reactivity was significantly associated with better QoL in MCI not HC. ALFF in the anterior cingulate cortex, medial prefrontal cortex (MPFC), and superior frontal gyrus (SFG) increased significantly less after cognitive tasks in MCI than HC. For the entire sample, greater increases of ALFF in MPFC and SFG were significantly associated with better QoL, and SFG alone significantly mediated the association between affective reactivity and QoL.

CONCLUSIONS

Enhancing SFG activation, especially among those with MCI, may provide a therapeutic target for addressing the negative impact of maladaptive affective regulation on QoL.

Cortical thickness is associated with altered autonomic function in cognitively impaired and non-impaired older adults

KEY POINTS

The parasympathetic nervous system (PNS) is critical for adaptation to environment demands. Alzheimer's disease (AD), via frontal compensatory processes, may affect PNS regulation, thereby compromising older adults' capacity for adaptation, and increasing morbidity and mortality risk. Here we found that AD-associated neurodegeneration accompanied an overactive anterior cingulate cortex, which in turn resulted in a high level of PNS activity at rest, as well as strong PNS activity withdrawal in response to the mental effort. This discovery provides the first line of evidence to suggest that AD-associated neurodegeneration links to altered PNS regulation during mental effort in older adults, and that the compensatory processes accompanying frontal hyperactivation appear to be responsible for these alterations.

ABSTRACT

The parasympathetic nervous system (PNS) is critical for adaptation to environment demands. PNS can reflect an individual's regulatory capacity of frontal brain regions and has been linked to cognitive capacity. Yet, the relationship of PNS function to cognitive decline and abnormal frontal function that characterize preclinical progression toward Alzheimer's disease (AD) is unclear. Here, we aimed to elucidate the relationship between PNS function and AD-associated neurodegeneration by testing two competing hypotheses involving frontal regions' activity (neurodegeneration vs. compensation). In 38 older human adults with amnestic mild cognitive impairment (aMCI) or normative cognition, we measured AD-associated neurodegeneration (AD signature cortical thickness; ADSCT), resting-state functional magnetic resonance imaging of frontal regions' spontaneous activation, and an electrocardiography measure of PNS (high frequency heart rate variability; HF-HRV). HF-HRV was assessed at rest and during a cognitive task protocol designed to capture HF-HRV reactivity. Higher HF-HRV at rest was significantly related to both more severe AD-associated neurodegeneration (lower ADSCT scores) and worse cognitive ability. Cognitive impairments were also related to greater suppression of HF-HRV reactivity. High activities of the anterior cingulate cortex significantly mediated relationships between ADSCT and both HF-HRV at rest and HF-HRV reactivity. Notably, these relationships were not affected by the clinical phenotype. We show that AD-associated neurodegeneration is associated with altered PNS regulation and that compensatory processes linked to frontal overactivation might be responsible for those alterations. This finding provides the first line of evidence in a new framework for understanding how early-stage AD-associated neurodegeneration affects autonomic regulation.

Aberrant Intrinsic Activity and Connectivity in Cognitively Normal Parkinson's Disease

Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson's disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological, rather than compensatory influence on cognitive abilities tested in this study. Receiver operating curve analyses demonstrated excellent sensitivity (≥90%) of rsfMRI variables in distinguishing patients from controls, but poor accuracy for brain volume and cognitive variables. Altogether these results provide new insights into the topology, cognitive relevance, and sensitivity of aberrant intrinsic activity and connectivity that precedes clinically significant cognitive impairment. Longitudinal studies are needed to determine if these neurocognitive associations presage the development of future mild cognitive impairment or dementia.