Keywords: Preclinical Image Analysis, Preclinical, Cortical network, Neighborhood disadvantage, Alzheimers disease

Motivation: Neighborhood disadvantage measured using an area deprivation index(ADI) has shown to impact cognitive outcomes,with alterations in regional volumetric and cortical assessment. Connectivity based approaches could further identify cortical network patterns associated with cognitive decline and neighborhood disadvantage

Goal(s): We evaluated associations between neighborhood disadvantage,cognitive impairment and changes in morphological similarity network(MSN)features.

Approach: For unimpaired cohort(n=297)with lowest and highest ADI ranks,cortical thickness based MSN features were computed and associations between ADI,cognitive performance and network features were assessed using linear regression and mediation analysis

Results: Disorganization of frontoparietal regions was associated with ADI and demonstrated marginal mediating effect between cognitive impairment and neighborhood disadvantage status.

Impact: Our findings of association between neighborhood disadvantage status and cortical disorganization in Alzheimer’s-related fronto-parietal brain regions, support the impact of neighborhood disadvantage on cognitive outcomes, and provide a connectivity based mechanism that may explain risk for cognitive decline and dementia.

Keywords: Functional Connectivity, fMRI (resting state), congenital deafness, functional magnetic resonance imaging, cochlear implantation

Motivation: To investigate the changes in low frequency fluctuation amplitude (mALFF) and regional homogeneity (ReHo) in the brains of children with congenital Sensorineural hearing loss (SNHL) by resting state fMRI.

Goal(s): The primary objective of this research was to improve understanding of the changes in neural functional activity within the cortical regions of SNHL patients during a resting state. 

Approach: The study's goal is to establish a neuroimaging pathological foundation, which could potentially provide significant neuroimaging biomarkers. 

Results: These biomarkers could aid in the clinical selection of appropriate candidates for cochlear implantation (CI), thereby enhancing the effectiveness of this therapeutic intervention.

Impact: The findings offer a fresh insight into the neuropathological mechanisms that drive functional reorganization in the cerebral cortex of children with congenital deafness after auditory deprivation. Moreover, these results provide valuable neuroimaging evidence for assessing the prognosis of post-CI patients.

Keywords: Functional Connectivity, Brain Connectivity, gradient

Motivation: Blind people are a good biological model for studying brain plasticity.

Goal(s): e examined the brain reorganization of the macroscale hierarchy in early-blind adolescents (EBA) compared with normal-sighted controls (NSC).

Approach: Twenty EBA and 20 age-and sex-matched NSC were included. We calculated the vertex-wise functional connectomes of each individual and compared the top 2 gradient scores between the EBA and NSC groups.

Results: The comparison between groups revealed increases in the first two gradients in the visual, sensorimotor, control, and default-mode networks in EBA.

Impact: The macroscale integration and segregation in unimodal and transmodal network is converged and strengthened in EBA relative to NSC.

Keywords: Functional Connectivity, fMRI (resting state)

Motivation: To explore the pathogenesis and functional abnormalities in visual center pathway in children with basic intermittent exotropia and develop an accurate approach for early diagnosis.

Goal(s): This study aims to uncover the neural basis of IXT by investigating the functional network alterations.

Approach: We used dynamic functional connectivity (dFC) analysis of resting state fMRI data to detect the brain network changes in IXT.

Results: Decreased dFC Variance between the left primary visual cortex and the left intermediate visual cortex, between the right ocular motor cortex and the right intermediate visual cortex were found in IXT children compared with HCs.

Impact: Our study was the first to investigate the dynamic brain network changes among primary visual cortex secondary visual cortex, and ocular motor cortex in IXT. This enhanced understanding of the neuropathological mechanisms underlying visual and oculomotor impairments in IXT children.

Keywords: fMRI Analysis, fMRI (resting state), Autism

Motivation: Neuroimaging analysis of brain functional changes can provide a new imaging perspective for understanding the neural mechanism and providing biomarkers for the clinical diagnosis of ASD.

Goal(s): This study aimed to explore the brain functional changes in children with autism spectrum disorder (ASD).

Approach: All subjects underwent brain resting state functional MRI (rs-fMRI) scans.The data were analyzed using various methods including functional segregation and functional integration.

Results: The results showed the significant higher and lower activities in many brain regions, hypo-connectivity between different brain networks and only hyper-connectivity between DAN and DMN.

Impact: The functional changes of the brain may be the pathogenesis for children with ASD accompanied, which could become the biomarkers in future clinical diagnosis.

Keywords: Functional Connectivity, Psychiatric Disorders, depression,adolescent,network

Motivation: The underlying mechanisms in adolescent-onset major depression disorder (AO-MDD) remains unclear with only few studies in small sample size. 

Goal(s): To investigate the alteration of functional connectivity (FC) in multiple networks in AO-MDD patients.

Approach: Seed-based analysis was conducted to detect the FC between AO-MDD group and healthy controls (HCs) at the regional and subregional level.

Results: Hypoconnectivity in AO-MDD was discovered in seeds including insula, amygdala, hippocampus, and their subregions which belong to salience network and affective network. The FC of the right insula and the left hippocampus correlated with the age of onset.

Impact: Our findings provided a comprehensive description of the altered connectivity in multiple networks at regional and subregional levels in AO-MDD pathogenesis. We demonstrated how age of onset contributes to AO-MDD symptomatology.

Keywords: Functional Connectivity, Brain, Major depressive disorder; resting state functional magnetic resonance imaging; network interaction index; functional network connectivity; dynamic functional network connectivity

Motivation: Major Depressive Disorder (MDD) has a high incidence and disability rate. However, the etiology remains unclear, and objective diagnostic markers are lacking. 

Goal(s): We hypothesize the presence of static and dynamic abnormal connectivity patterns in three core networks of MDD patients. 

Approach: We employ static functional network connectivity (FNC) analysis, dynamic functional network connectivity (dFNC), the network interaction index (NII), and the dynamic functional network connectivity (dNII) to investigate interactions among Default Mode Network (DMN), Salience Network (SN), and Executive Control Network (ECN).

Results: MDD patients have abnormal network functional interactions that can be captured by static and dynamic NII indicators. 

Impact: The abnormal network functional interactions deepen our understanding of the abnormal activity of the three networks in MDD patients, helps to reveal the pathogenesis of MDD, and provides ideas for its intervention.

Keywords: Functional Connectivity, fMRI (resting state)

Motivation: The motivation is to explore the influence of onset age on large-scale brain networks in MDD patients.

Goal(s): The purpose of this study is to explore the shared and unique alterations of large-scale network connectivity between adolescent-onset and adult-onset MDD.

Approach: This was a single-center cross-sectional study. Volunteers underwent R-fMRI scans. The 2×2 ANOVA was used to analyze the main effects of diagnosis, age and their interaction effect on FCs.

Results: Adolescent-onset and adult-onset MDD have shared and unique large-scale network alterations. The shared altered FCs included VN, LN, VN-DAN VN-LN and LN-DMN. The unique altered FCs included DAN and LN.

Impact: Our findings provide the physiological mechanisms of adolescent-onset and adult-onset MDD for improving clinical subtyping and treatment strategies. The results also suggested that when we explore biomarkers of MDD, we should include onset age as a consideration. 

Keywords: Functional Connectivity, Psychiatric Disorders, subthreshold depression

Motivation: identifying the neural pathology mechanisms has the potential value to elucidate risk factors and prognostic markers for subthreshold depression(StD)

Goal(s): FNC is a useful imaging tool in detecting the neuro-mechanism of the brain 

Approach: This study involved in the static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) to investigate the FNCdifferences between the StD and HCs groups

Results: StD demonstrated altered FNC in executive control network (ECN), default mode network (DMN), sensorimotor network (SMN) and dorsal attentional network (DAN), in addition, Std had increased mean dwell time and fraction time in a weak connected state concerning the dFNC analysis. 

Impact: The sFNC and dFNC findings could enrich our understanding of the large-scale resting-state FNC abnormalities in StD individuals, which could provide insights for a better understanding of the behind neural mechanisms

Keywords: Functional Connectivity, Brain Connectivity, Glioma; fMRI

Motivation: Gliomas affect the whole brain causing widespread network modifications.

Goal(s): This study investigated the tumor effect on multiple brain networks using resting-state functional MRI.

Approach: 147 glioma patients and 200 healthy controls (HCs) were included. After pre-processing, group-independent and group information-guided component analyses were used to extract brain networks. The cosine similarity of each patient’s network was compared to HCs. Chi-squared test was used to test associations with tumor location and grade.

Results: Cognitive networks are selectively vulnerable to tumor growth. Functional alterations extend beyond tumor boundaries, and increase with WHO-grade. Tumor location in known eloquent areas exerts widespread effects on brain networks.

Impact: We developed a methodology to quantify tumor-induced alterations of individual brain networks. These alterations extend beyond tumor boundaries, vary with network’s function, tumor location and grade. Understanding such abnormalities is crucial for managing cognitive disabilities before and after surgery.

Keywords: Functional Connectivity, Inflammation

Motivation: Patients with chronic rhinosinusitis (CRS) have an increased risk of emotional and cognitive disorders. 

Goal(s): We aim to explore the neural mechanisms in CRS patients using the voxel-wise degree centrality (DC) approach. 

Approach: Here we collected resting-state functional MRI data to assess the voxel-wise DC values in patients with CRS. 

Results:  Compared with HCs, CRS patients indicated decreased DC values in the right precuneus and increased DC values in the left inferior temporal gyrus (ITG). In addition, a positive correlation between the DC values in the left inferior temporal gyrus and disease duration was observed. 

Impact: CRS patients showed intrinsic abnormal DC values in the right precuneus and the left ITG, both of which are involved in cognitive processing and emotional regulation. These results reveal new insights into the neuropathological mechanisms in CRS patients.

Keywords: fMRI Analysis, fMRI (resting state), Brain Oxygen Consumption, Neural Network

Motivation: Calibrated BOLD-arterial spin labelling (ASL) fMRI exploits isometabolic hypercapnic changes of brain physiology to map grey matter maximum BOLD modulation (M) and, through biophysical modelling, estimate the oxygen extraction fraction and the cerebral metabolic rate of oxygen. However, this approach requires a CO₂ gas-challenge or breath-holding, limiting its clinical application. 

Goal(s): It would be ideal to estimate M from low SNR, non-isometabolic resting-state (RS) BOLD-ASL fluctuations. 

Approach: We investigate the ability of a frequency-domain, data-driven, neural network approach to estimate the physiological parameters of interest from RS data in comparison to a breath-hold approach.  

Results: The proposed approach can map the desired parameters.

Impact: The ability to map oxygen consumption in the grey matter through resting state data using a calibrated fMRI framework would allow a  simple implementation of such an approach in research settings paving the way to its utilization in clinical practice.

Keywords: Data Processing, Brain Connectivity

Motivation: Regional Homogeneity (ReHO) of BOLD signal is a potential marker of brain activity at rest. CBF is coupled to metabolism in the human brain and it can be used to investigate the physiological significance of ReHo.

Goal(s): We aimed to assess the spatial correlation between ReHo and ASL-derived CBF and its temporal stability.

Approach: Twenty subjects underwent 28 minutes of simultaneously acquired BOLD-ASL resting-state fMRI. CBF and ReHo spatial associations at different times were estimated and compared.

Results: We found a modest but stable and significant spatial correlation between CBF and ReHo.

Impact: This study could be significant for diagnosis and treatment of neurological disorders. If ReHo is demonstrated to be a reliable marker of local brain metabolism, it could be used to develop new fMRI methods for detecting and monitoring brain disorders.

Keywords: Vascular, Vessels

Motivation: There is a lack of head-to-head evaluation of resting-state (RS) and breath-hold (BH) cerebrovascular reactivity (CVR).

Goal(s): Propose an integrated paradigm combining RS- and BH-BOLD acquisition in a single run, and evaluate the reliability of RS- and BH-CVR mapping with this protocol.

Approach: Combined RS- and BH-BOLD data were acquired on a 7T scanner. CVR mappings of various time windows were calculated and compared.

Results: RS-BOLD can be calculated for CVR mapping but is susceptible to BOLD signal outliers. BH-BOLD produces stable CVR mappings with higher dynamic range. The integrated paradigm guarantees reliable BH-CVR mapping and RS-fMRI analysis.

Impact: The introduction of the RS-BH paradigm offers an avenue for reliable CVR mapping with high dynamic range and is compatible with conventional RS-fMRI analysis.

Keywords: Functional Connectivity, fMRI (resting state), Parcellation, Cohesion, DCBC

Motivation: Cohesive parcellation provides optimal connectivity-based parcels for downstream brain modeling, but at the cost of high parcel count, making comparisons to traditional parcellations difficult.

Goal(s): We aim to fairly compare parcellations across a wide array of parcel sizes and counts.

Approach: rsfMRI of 18 healthy subjects were parcellated based on cohesion and evaluated with the distance-controlled boundary coefficient (DCBC), an unbiased metric that incorporates spatial features of parcels in addition to connectivity.

Results: Cohesive parcellation compared favorably to traditional parcellations based on DCBC of rsfMRI.

Impact: Using an unbiased metric (DCBC), we show that the utility of connectivity-based cohesive parcellation is not simply due to high parcel count.