Shared and Specific Changes of Cortico-Striatal Functional Connectivity in Stable Mild Cognitive Impairment and Progressive Mild Cognitive Impairment.

Background: Mild cognitive impairment (MCI), the prodromal stage of Alzheimer's disease, has two distinct subtypes: stable MCI (sMCI) and progressive MCI (pMCI). Early identification of the two subtypes has important clinical significance. Objective: We aimed to compare the cortico-striatal functional connectivity (FC) differences between the two subtypes of MCI and enhance the accuracy of differential diagnosis between sMCI and pMCI. Methods: We collected resting-state fMRI data from 31 pMCI patients, 41 sMCI patients, and 81 healthy controls. We chose six pairs of seed regions, including the ventral striatum inferior, ventral striatum superior, dorsal-caudal putamen, dorsal-rostral putamen, dorsal caudate, and ventral-rostral putamen and analyzed the differences in cortico-striatal FC among the three groups, additionally, the relationship between the altered FC within the MCI subtypes and cognitive function was examined. Results: Compared to sMCI, the pMCI patients exhibited decreased FC between the left dorsal-rostral putamen and right middle temporal gyrus, the right dorsal caudate and right inferior temporal gyrus, and the left dorsal-rostral putamen and left superior frontal gyrus. Additionally, the altered FC between the right inferior temporal gyrus and right putamen was significantly associated with episodic memory and executive function. Conclusions: Our study revealed common and distinct cortico-striatal FC changes in sMCIs and pMCI across different seeds; these changes were associated with cognitive function. These findings can help us understand the underlying pathophysiological mechanisms of MCI and distinguish pMCI and sMCI in the early stage potentially.

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

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

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

BACKGROUND: Cerebral small vessel disease (CSVD) is considered an age-related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD-M) or without (CSVD-W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration. METHODS: Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting-state functional MRI (rs-fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two-sample t-test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p < .05). RESULTS: Compared with HCs, the CSVD-M group indicated decreased sALFF values in the bilateral cerebellum posterior lobe (CPL) and the left inferior Parietal Lobule (IPL), with increased sALFF values in the right SFG. For dALFF analysis, the CSVD-W group had significant dALFF variability in the right fusiform gyrus compared with HC. Moreover, the postcentral gyrus (PoCG) was significantly high in the CSVD-W group. While in the CSVD-M group, the bilateral paracentral lobules (PL) revealed significantly elevated dALFF variability and low dALFF variability in the left CPL and right IPL compared with HCs. The CSVD-M group had high dALFF variability in the bilateral PL but low dALFF variability in the left middle temporal gyrus (MTG) and right PoCG compared with the CSVD-W group. The partial correlation analysis indicated that dALFF variability in the left MTG was positively associated with EM (r = 0.713, p = .002) in CSVD-W and CSVD-M groups. In the groups with CSVD-M and HC, altered dALFF variability in the bilateral PL was negatively correlated with EM (r = -0.560, p = .002). CONCLUSION: There were significant changes in sALFF and dALFF variability in CSVD patients. Abnormal spontaneous static and dynamic ALFFs may provide new insights into cognitive dysfunction in CSVD with MCI and may be valuable biomarkers for early diagnosis.

Functional changes in the salience network of patients with amnesic mild cognitive impairment before and after repetitive transcranial magnetic stimulation.

BACKGROUND: Amnestic mild cognitive impairment (aMCI) is considered to be the prodromal stage of Alzheimer's disease (AD). The precuneus (PCUN) may be an imaging marker for monitoring the progression of AD. Meanwhile, cognitive impairment in AD patients is closely related to functional connectivity (FC) changes in the salience network (SN). We hypothesize that there are specific neuroimaging biomarkers in the SN and that FC changes in aMCI patients after repetitive transcranial magnetic stimulation (rTMS) intervention are associated with cognitive function. The purpose of this study was to first investigate the pattern of functional changes in aMCI patients and healthy controls (HCs) and then compare the functional changes in aMCI patients before and after rTMS targeting to PCUN and its correlation with cognitive function. METHODS: Thirty-six HCs and 61 aMCIs were recruited for our study. Eleven people in the aMCI group received rTMS intervention 5 days a week for 4 weeks. Using the right anterior insula as the seed-of-interest, we first compared FC changes in HC and aMCI patients and then compared cognitive function in aMCI patients before and after rTMS. The above is the functional connection analysis of seed-to-voxel. Moreover, we investigated the FC changes in aMCI patients after rTMS intervention and its correlation with cognitive function. RESULTS: Compared with HC, the aMCI group showed altered FC in bilateral parahippocampal gyrus, bilateral inferior parietal lobule, left middle frontal gyrus, and left middle temporal gyrus. Moreover, rTMS at PCUN improved the cognitive function of aMCI patients, which was related to the altered FC in posterior cerebellar lobes (CPL). CONCLUSIONS: Our findings suggest that rTMS targeting PCUN is a promising, noninvasive approach to ameliorating cognitive dysfunction in aMCI patients, and that this cognitive improvement is accompanied by brain connectivity modulation.

Evidence of functional abnormalities in the default mode network in bipolar depression: A coordinate-based activation likelihood estimation meta-analysis.

BACKGROUND: The default mode network (DMN) is thought to be involved in the pathophysiology of bipolar depression (BD). However, the findings of prior studies on DMN alterations in BD are inconsistent. Thus, this study aimed to systematically investigate functional abnormalities of the DMN in BD patients. METHODS: We systematically searched PubMed, Ovid, and Web of Science for functional neuroimaging studies on regional homogeneity, amplitude of low frequency fluctuations (ALFF), and functional connectivity of the DMN in BD patients published before March 18, 2022. The stereotactic coordinates of the reported altered brain regions were extracted and incorporated into a brain map using the coordinate-based activation likelihood estimation approach. RESULTS: A total of 43 original research studies were included in the meta-analysis. BD patients showed specific changes in the DMN including decreased ALFF/fractional ALFF in the left cingulate gyrus (CG) and bilateral precuneus (PCUN); increased functional connectivity (FC) in the left CG, left posterior CG, left PCUN, bilateral medial frontal gyrus, and bilateral superior frontal gyrus; and decreased FC in the left CG, left PCUN, left inferior parietal lobule, and left postcentral gyrus. LIMITATIONS: Conclusions are limited by the small number of studies, additional meta-analyses are needed to obtain more data in BD subgroup. CONCLUSION: This meta-analysis supports specific changes in DMN activity and FC in BD patients, which may be powerful biomarkers for the diagnosis of BD. The CG and PCUN were the most affected regions and are thus potential targets for clinical interventions to delay BD progression.

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.

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.

Altered Patterns of Amplitude of Low-Frequency Fluctuations and Fractional Amplitude of Low-Frequency Fluctuations Between Amnestic and Vascular Mild Cognitive Impairment: An ALE-Based Comparative Meta-Analysis.

Background: Changes in the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF) have provided stronger evidence for the pathophysiology of cognitive impairment. Whether the altered patterns of ALFF and fALFF differ in amnestic cognitive impairment (aMCI) and vascular mild cognitive impairment (vMCI) is largely unknown. The purpose of this study was to explore the ALFF/fALFF changes in the two diseases and to further explore whether they contribute to the diagnosis and differentiation of these diseases. Methods: We searched PubMed, Ovid, and Web of Science databases for articles on studies using the ALFF/fALFF method in patients with aMCI and vMCI. Based on the activation likelihood estimation (ALE) method, connectivity modeling based on coordinate meta-analysis and functional meta-analysis was carried out. Results: Compared with healthy controls (HCs), patients with aMCI showed increased ALFF/fALFF in the bilateral parahippocampal gyrus/hippocampus (PHG/HG), right amygdala, right cerebellum anterior lobe (CAL), left middle temporal gyrus (MTG), left cerebrum temporal lobe sub-gyral, left inferior temporal gyrus (ITG), and left cerebrum limbic lobe uncus. Meanwhile, decreased ALFF/fALFF values were also revealed in the bilateral precuneus (PCUN), bilateral cuneus (CUN), and bilateral posterior cingulate (PC) in patients with aMCI. Compared with HCs, patients with vMCI predominantly showed decreased ALFF/fALFF in the bilateral CUN, left PCUN, left PC, and right cingulate gyrus (CG). Conclusions: The present findings suggest that ALFF and fALFF displayed remarkable altered patterns between aMCI and vMCI when compared with HCs. Thus, the findings of this study may serve as a reliable tool for distinguishing aMCI from vMCI, which may help understand the pathophysiological mechanisms of these diseases.

Aberrant functional connectivity and activity in Parkinson's disease and comorbidity with depression based on radiomic analysis.

INTRODUCTION: The current diagnosis of Parkinson's disease (PD) comorbidity with depression (DPD) largely depends on clinical evaluation. However, the modality may tend to lack precision in detecting PD with depression. A radiomic approach that combines functional connectivity and activity with clinical scores has the potential to achieve accurate and differential diagnosis between PD and DPD. METHODS: In this study, we aimed to employ the radiomic approach to extract large-scale features of functional connectivity and activity for differentiating among DPD, PD with no depression (NDPD), and healthy controls (HC). We extracted 6,557 features of five types from all subjects including clinical characteristics, resting-state functional connectivity (RSFC), amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC). Lasso, random forest, and support vector machine (SVM) were implemented for feature selection and dimension reduction based on the training sets, and the prediction performance for different methods in the testing sets was compared. RESULTS: The results showed that nineteen features were selected for the group of DPD versus HC, 34 features were selected for the group of NDPD versus HC, and 17 features were retained for the group of DPD versus NDPD. In the testing sets, Lasso prediction achieved the accuracies of 0.95, 0.96, and 0.85 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Random forest achieved the accuracies of 0.90, 0.82, and 0.90 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively, while SVM yielded the accuracies of 1, 0.86 and 0.65 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. CONCLUSIONS: By identifying aberrant functional connectivity and activity as potential biomarkers, the radiomic approach facilitates a deeper understanding and provides new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.