Resting-state Functional Networks Research Articles

Towards personalized precision functional mapping in infancy

Abstract The precise network topology of functional brain systems is highly specific to individuals and undergoes dramatic changes during critical periods of development. Large amounts of high-quality resting state data are required to investigate these individual differences, but are difficult to obtain in early infancy. Using the template matching method, we generated a set of infant network templates to use as priors for individualized functional resting-state network mapping in two independent neonatal datasets with extended acquisition of resting-state functional MRI (fMRI) data. We show that template matching detects all major adult resting-state networks in individual infants and that the topology of these resting-state network maps is individual-specific. Interestingly, there was no plateau in within-subject network map similarity with up to 25 minutes of resting-state data, suggesting that the amount and/or quality of infant data required to achieve stable or high-precision network maps is higher than adults. These findings are a critical step towards personalized precision functional brain mapping in infants, which opens new avenues for clinical applicability of resting-state fMRI and potential for robust prediction of how early functional connectivity patterns relate to subsequent behavioral phenotypes and health outcomes.

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Minimum spanning tree analysis of EEG resting-state functional networks in schizophrenia

Schizophrenia is a serious and complex mental disease, known to be associated with various subtle structural and functional deviations in the brain. Recently, increased attention is given to the analysis of brain-wide, global mechanisms, strongly altering the communication of long-distance brain areas in schizophrenia. Data of 32 patients with schizophrenia and 28 matched healthy control subjects were analyzed. Two minutes long 64-channel EEG recordings were registered during resting, eyes closed condition. Average connectivity strength was estimated with Weighted Phase Lag Index (wPLI) in lower frequencies: delta and theta, and Amplitude Envelope Correlation with leakage correction (AEC-c) in higher frequencies: alpha, beta, lower gamma and higher gamma. To analyze functional network topology Minimum Spanning Tree (MST) algorithms were applied. Results show that patients have weaker functional connectivity in delta and alpha frequency bands. Concerning network differences, the result of lower diameter, higher leaf number, and also higher maximum degree and maximum betweenness centrality in patients suggest a star-like, and more random network topology in patients with schizophrenia. Our findings are in accordance with some previous findings based on resting-state EEG (and fMRI) data, suggesting that MST network structure in schizophrenia is biased towards a less optimal, more centralized organization.

Decreased resting-state functional connectivity and brain network abnormalities in the prefrontal cortex of elderly patients with Parkinson's disease accompanied by depressive symptoms.

This study aimed to explore the brain network characteristics in elderly patients with Parkinson's disease (PD) with depressive symptoms. Thirty elderly PD patients with depressive symptoms (PD-D) and 26 matched PD patients without depressive symptoms (PD-NOD) were recruited based on HAMD-24 with a cut-off of 7. The resting-state functional connectivity (RSFC) was conducted by 53-channel functional near-infrared spectroscopy (fNIRS). There were no statistically significant differences in MMSE scores, disease duration, Hoehn-Yahr stage, daily levodopa equivalent dose, and MDS-UPDRS III between the two groups. However, compared to the PD-NOD group, the PD-D group showed significantly higher MDS-UPDRS II, HAMA-14, and HAMD-24. The interhemispheric FC strength and the FC strength between the left dorsolateral prefrontal cortex (DLPFC-L) and the left frontal polar area (FPA-L) was significantly lower in the PD-D group (FDR p < 0.05). As for graph theoretic metrics, the PD-D group had significantly lower degree centrality (aDc) and node efficiency (aNe) in the DLPFC-L and the FPA-L (FDR, p < 0.05), as well as decreased global efficiency (aEg). Pearson correlation analysis indicated moderate negative correlations between HAMD-24 scores and the interhemispheric FC strength, FC between DLPFC-L and FPA-L, aEg, aDc in FPA-L, aNe in DLPFC-L and FPA-L. In conclusion, PD-D patients show decreased integration and efficiency in their brain networks. Furthermore, RSFC between DLPFC-L and FPA-L regions is negatively correlated with depressive symptoms. These findings propose that targeting DLPFC-L and FPA-L regions via non-invasive brain stimulation may be a potential intervention for alleviating depressive symptoms in elderly PD patients.

Brain network entropy, depression, and quality of life in people with traumatic brain injury and seizure disorders.

Traumatic brain injury (TBI) often precedes the onset of epileptic (ES) or psychogenic nonepileptic seizures (PNES) with depression being a common comorbidity. The relationship between depression severity and quality of life (QOL) may be related to resting-state network complexity. We investigated these relationships in adults with TBI-only, TBI + ES, or TBI + PNES using Sample Entropy (SampEn), a measure of physiologic signals complexity. Adults with TBI-only (n = 60), TBI + ES (n = 21), or TBI + PNES (n = 56) completed the Beck Depression Inventory-II (BDI-II; depression symptom severity) and QOL in Epilepsy (QOLIE-31) assessments and underwent resting-state functional magnetic resonance imaging (rs-fMRI). SampEn values derived from six resting state functional networks were calculated per participant. Effects of group, network, and group-by-network-interactions for SampEn were investigated with a mixed-effects model. We examined relationships between BDI-II, QOL, and SampEn of each of the networks. Groups did not differ in age, but there was a higher proportion of women with TBI + PNES (p = 0.040). TBI + ES and TBI-only groups did not differ in BDI-II or QOLIE-31 scores, while the TBI + PNES group scored worse on both measures. The fixed effects of the model revealed significant differences in SampEn values across networks (lower SampEn for the frontoparietal network compared to other networks). The likelihood ratio test for group-by-network-interactions was significant (p = 0.033). BDI-II was significantly negatively associated with Overall QOL scale scores in all groups, and significantly negatively associated with network SampEn values only in the TBI + PNES group. Only TBI + PNES had significant relationships between depression symptom severity and network SampEn values indicating that the resting state network complexity is related to depression severity in this group but not in TBI + ES or TBI-only. The brain has a complex network of internal connections. How well these connections work may be affected by TBI and seizures and may underlie mental health symptoms including depression; the worse the depression, the worse the quality of life. Our study compared brain organization in people with TBI, people with epilepsy after TBI, and people with nonepileptic seizures after TBI. Only people with nonepileptic seizures after TBI showed a relationship between how organized their brain connections were and how bad was their depression. We need to better understand these relationships to develop more impactful, effective treatments.

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study.

Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia. In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined. Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions. The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

Effects of second language acquisition on brain functional networks at different developmental stages.

Previous studies have shown that language acquisition influences both the structure and function of the brain. However, whether the acquisition of a second language at different periods of life alters functional network organization in different ways remains unclear. Here, functional magnetic resonance imaging data from 27 English-speaking monolingual controls and 52 Spanish-English bilingual individuals, including 22 early bilinguals who began learning a second language before the age of ten and 30 late bilinguals who started learning a second language at age fourteen or later, were collected from the OpenNeuro database. Topological metrics of resting-state functional networks, including small-world attributes, network efficiency, and rich- and diverse-club regions, that characterize functional integration and segregation of the networks were computed via a graph theoretical approach. The results showed obvious increases in network efficiency in early bilinguals and late bilinguals relative to the monolingual controls; for example, the global efficiency of late bilinguals and early bilinguals was improved relative to that of monolingual controls, and the local efficiency of early bilinguals occupied an intermediate position between that of late bilinguals and monolingual controls. Obvious increases in rich-club and diverse-club functional connectivity were observed in the bilinguals relative to the monolingual controls. Three network metrics were positively correlated with Spanish proficiency test scores. These findings demonstrated that early and late acquisition of a second language had different impacts on the functional networks of the brain.

Topological features of functional brain networks and subclinical impulsivity: an investigation in younger and older adults.

Impulsive traits (i.e., the tendency to act without forethought regardless of negative outcomes) are frequently found in healthy populations. When exposed to risk factors, individuals may develop debilitating disorders of impulse control (addiction, substance abuse, gambling) characterized by behavioral and cognitive deficits, eventually leading to huge socioeconomic costs. With the far-reaching aim of preventing the onset of impulsive disorders, it is relevant to investigate the topological organization of functional brain networks associated with impulsivity in sub-clinical populations. Taking advantage of the open-source LEMON dataset, we investigated the topological features of resting-state functional brain networks associated with impulsivity in younger (n=146, age: 20-35) and older (n=61, age: 59-77) individuals, using a graph-theoretical approach. Specifically, we computed indices of segregation and integration at the level of specific circuits and nodes known to be involved in impulsivity (frontal, limbic, and striatal networks). In younger individuals, results revealed that impulsivity was associated with a more widespread, less clustered and less efficient functional organization, at all levels of analyses and in all selected networks. Conversely, impulsivity in older individuals was associated with reduced integration and increased segregation of striatal regions. Speculatively, such alterations of functional brain networks might underlie behavioral and cognitive abnormalities associated with impulsivity, a working hypothesis worth being tested in future research. Lastly, differences between younger and older individuals might reflect the implementation of age-specific adaptive strategies, possibly accounting for observed differences in behavioral manifestations. Potential interpretations, limitations and implications are discussed.

Alterations of resting-state functional network connectivity in patients with noise-induced hearing loss: A study based on independent component analysis.

Functional reorganization is a response to auditory deficits or deprivation, and less is known about the overall brain network alterations involving resting-state networks (RSNs) and multiple functional networks in patients with occupational noise-induced hearing loss (NIHL). So this study evaluated resting-state functional network connectivity (FNC) alterations in occupational NIHL using an independent component analysis (ICA). In total, 79 mild NIHL patients (MP), 32 relatively severe NIHL patients (RSP), and 84 age- and education- matched healthy controls (HC) were recruited. All subjects were tested using the Mini-mental State Examination scale, the tinnitus Handicap Inventory scale, the Hamilton Anxiety scale (HAMA) and scanned by T1-3DFSPGR, resting-state functional magnetic resonance imaging sequence in 3.0 T and analysed by the ICA. Seven RSNs were identified, compared with the HC, the MP showed increased FNC within the executive control network (ECN) and enhanced FNC within the default mode network (DMN) and the visual network (VN); compared with the HC, the RSP showed decreased FNC within the ECN and auditory network (AUN), DMN and VN; no significant changes in FNC were found in the MP compared with the RSP. Furthermore, the correlation analysis between the noise exposure time and hearing loss level, HAMA were both negative, and there were no significant correlations between the abnormal RSNs and the hearing level, noise exposure time and HAMA. These findings indicate that different degrees of NIHL involve different alterations in RSNs connectivity and may reveal the neural mechanisms related to emotion-related features and functional abnormalities following long-term NIHL.

Altered resting-state brain functional activities and networks in Crohn’s disease: a systematic review

BackgroundCrohn’s disease (CD) is a non-specific chronic inflammatory disease of the gastrointestinal tract and is a phenotype of inflammatory bowel disease (IBD). The current study sought to compile the resting-state functional differences in the brain between CD patients and healthy controls.MethodsThe online databases PubMed, Web of Science Core, and EMBASE were used to find the published neuroimage studies. The search period was from the beginning through December 15, 2023. The predetermined inclusion and exclusion criteria allowed for the identification of the studies. The studies were assembled by two impartial reviewers, who also assessed their quality and bias.ResultsThis review comprised 16 resting-state fMRI studies in total. The included studies generally had modest levels of bias. According to the research, emotional processing and pain processing were largely linked to increased or decreased brain activity in patients with CD. The DMN, CEN, and limbic systems may have abnormalities in patients with CD, according to research on brain networks. Several brain regions showed functional changes in the active CD group compared to the inactive CD group and the healthy control group, respectively. The abnormalities in brain areas were linked to changes in mood fluctuations (anxiety, melancholy) in patients with CD.ConclusionFunctional neuroimaging helps provide a better understanding of the underlying neuropathological processes in patients with CD. In this review, we summarize as follows: First, these findings indicate alterations in brain function in patients with CD, specifically affecting brain regions associated with pain, emotion, cognition, and visceral sensation; second, disease activity may have an impact on brain functions in patients with CD; and third, psychological factors may be associated with altered brain functions in patients with CD.

Aberrant brain functional hubs and causal effective connectivity in menstrually-related and non-menstrually-related migraine without aura.

Menstrual migraine without aura (MRM) is common in female migraineurs and is closely related to cerebral functional abnormalities. However, whether the whole brain networks and directional functional connectivity of MRM patients are altered remains unclear. The purpose of this study was to detect the alterations of resting-state functional networks and directional functional connectivity between MRM and non-menstrual migraine without aura (NMM) patients using functional magnetic resonance imaging (fMRI) with degree centrality (DC) and Granger causality analysis (GCA) methods. In this retrospective and cross-sectional study, 45 MRM and 40 NMM patients (matched in age, gender, and years of education) were recruited in the study between May 2018 and June 2022. All participants had undergone resting-state fMRI scanning at the Neurology and Pain Outpatient Department of Nanjing First Hospital. Their brain functions were analyzed in terms of DC and GCA, with the significant threshold at voxel level P<0.01 and cluster level P<0.05, Gaussian random field corrected. Correlation analysis was adopted to assess the relationships between the fMRI results and clinical features (P<0.05, Bonferroni corrected). Compared with those in the NMM group, MRM patients showed decreased DC in the right insula (T=-4.253). Using the right insula as the seed region, patients with MRM demonstrated enhanced effective connectivity from the right insula to the ipsilateral middle temporal gyrus (T=4.138) and contralateral superior temporal gyrus (T=3.523). Furthermore, the MRM group also showed decreased effective connectivity from several brain regions to the right insula, which included the right inferior occipital gyrus (T=-4.498), left middle frontal gyrus (T=-4.879), right precuneus (T=-4.644), and left inferior parietal gyrus (T=-4.113). The average Self-rating Anxiety Scale score of the MRM group was significantly higher than that of the NMM group [P=0.032, 95% confidence interval (CI): 0.363-7.761]. In the MRM group, disease duration was negatively correlated with the mean value of DC in right insula (r=-0.428, P=0.01). The present research demonstrated that patients with MRM have disruption in insula resting-state functional networks. Disrupted networks contained regions associated with cognitive processes, emotional perception, and migraine attack in MRM patients. These results may improve our comprehension of the neuromechanism of menstrually-related migraine.

Age-related differences in structural and resting-state functional brain network organization across the adult lifespan: A cross-sectional study

We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity.Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain's medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased between-network RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the language-auditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.

North Korean defectors with PTSD and complex PTSD show alterations in default mode network resting-state functional connectivity.

North Korean defectors (NKDs) have often been exposed to traumatic events. However, there have been few studies of neural alterations in NKDs with post-traumatic stress disorder (PTSD) and complex PTSD (cPTSD). To investigate neural alterations in NKDs with PTSD and cPTSD, with a specific focus on alterations in resting-state functional connectivity networks, including the default mode network (DMN). Resting-state functional connectivity was assessed using brain functional magnetic resonance imaging in three groups of NKDs: without PTSD, with PTSD and with cPTSD. Statistical tests were performed, including region of interest (ROI)-to-ROI and ROI-to-voxel analysis, followed by post hoc correlation analysis. In the ROI-to-ROI analysis, differences in functional connectivity were found among the components of the DMN, as well as in the thalamus and the basal ganglia. Right hippocampus-left pallidum and right amygdala-left lingual gyrus connectivity differed between groups in the ROI-to-voxel analysis, as did connectivity involving the basal ganglia. The post hoc analysis revealed negative correlations between Coping and Adaptation Processing Scale (CAPS) score and left posterior cingulate cortex-right pallidum connectivity and between CAPS score and right putamen-left angular gyrus connectivity in the control group, which were not observed in other groups. The results suggest that there are alterations in the functional connectivity of the DMN and the limbic system in NKDs with PTSD and cPTSD, and that these alterations involve the basal ganglia. The lower correlations of CAPS score with right basal ganglia-DMN functional connectivity in patients compared with controls further implies that these connectivities are potential targets for treatment of PTSD and cPTSD.

Transcriptional signatures of the whole-brain voxel-wise resting-state functional network centrality alterations in schizophrenia

Neuroimaging studies have revealed that patients with schizophrenia exhibit disrupted resting-state functional connectivity. However, the inconsistent findings across these studies have hindered our comprehensive understanding of the functional connectivity changes associated with schizophrenia, and the molecular mechanisms associated with these alterations remain largely unclear. A quantitative meta-analysis was first conducted on 21 datasets, involving 1057 patients and 1186 healthy controls, to examine disrupted resting-state functional connectivity in schizophrenia, as measured by whole-brain voxel-wise functional network centrality (FNC). Subsequently, partial least squares regression analysis was employed to investigate the relationship between FNC changes and gene expression profiles obtained from the Allen Human Brain Atlas database. Finally, gene enrichment analysis was performed to unveil the biological significance of the altered FNC-related genes. Compared with healthy controls, patients with schizophrenia show consistently increased FNC in the right inferior parietal cortex extending to the supramarginal gyrus, angular gyrus, bilateral medial prefrontal cortex, and right dorsolateral prefrontal cortex, while decreased FNC in the bilateral insula, bilateral postcentral gyrus, and right inferior temporal gyrus. Meta-regression analysis revealed that increased FNC in the right inferior parietal cortex was positively correlated with clinical score. In addition, these observed functional connectivity changes were found to be spatially associated with the brain-wide expression of specific genes, which were enriched in diverse biological pathways and cell types. These findings highlight the aberrant functional connectivity observed in schizophrenia and its potential molecular underpinnings, providing valuable insights into the neuropathology of dysconnectivity associated with this disorder.

Resting-State Functional Magnetic Resonance Imaging Network Association With Mortality, Epilepsy, Cognition, and Motor Two-Year Outcomes in Suspected Severe Neonatal Acute Brain Injury

Background and ObjectivesIn acute brain injury of neonates, resting-state functional magnetic resonance imaging (MRI) (RS) showed incremental association with consciousness, mortality, cognitive and motor development, and epilepsy, with correction for multiple comparisons, at six months postgestation in neonates with suspected acute brain injury (ABI). However, there are relatively few developmental milestones at six months to benchmark against, thus, we extended this cohort study to evaluate two-year outcomes. MethodsIn 40 consecutive neonates with ABI and RS, ordinal scores of resting-state networks; MRI, magnetic resonance spectroscopy, and electroencephalography; and up to 42-month outcomes of mortality, general and motor development, Pediatric Cerebral Performance Category Scale (PCPC), and epilepsy informed associations between tests and outcomes. ResultsMean gestational age was 37.8 weeks, 68% were male, and 60% had hypoxic-ischemic encephalopathy. Three died in-hospital, four at six to 42 months, and five were lost to follow-up. Associations included basal ganglia network with PCPC (P = 0.0003), all-mortality (P = 0.005), and motor (P = 0.0004); language/frontoparietal network with developmental delay (P = 0.009), PCPC (P = 0.006), and all-mortality (P = 0.01); default mode network with developmental delay (P = 0.003), PCPC (P = 0.004), neonatal intensive care unit mortality (P = 0.01), and motor (P = 0.009); RS seizure onset zone with epilepsy (P = 0.01); and anatomic MRI with epilepsy (P = 0.01). ConclusionFor the first time, at any age, resting state functional MRI in ABI is associated with long-term epilepsy and RSNs predicted mortality in neonates. Severity of RSN abnormality was associated with incrementally worsened neurodevelopment including cognition, language, and motor function over two years.

Fragmentation of functional resting state brain networks in a transgenic mouse model of tau pathology: A metabolic connectivity study using [18F]FDG-PET

In a previous study, regional reductions in cerebral glucose metabolism have been demonstrated in the tauopathy mouse model rTg4510 (Endepols et al., 2022). Notably, glucose hypometabolism was present in some brain regions without co-localized synaptic degeneration measured with [18F]UCB-H. We hypothesized that in those regions hypometabolism may reflect reduced functional connectivity rather than synaptic damage. To test this hypothesis, we performed seed-based metabolic connectivity analyses using [18F]FDG-PET data in this mouse model. Eight rTg4510 mice at the age of seven months and 8 non-transgenic littermates were injected intraperitoneally with 11.1 ± 0.8 MBq [18F]FDG and spent a 35-min uptake period awake in single cages. Subsequently, they were anesthetized and measured in a small animal PET scanner for 30 min. Three seed-based connectivity analyses were performed per group. Seeds were selected for apparent mismatch between [18F]FDG and [18F]UCB-H. A seed was placed either in the medial orbitofrontal cortex, dorsal hippocampus or dorsal thalamus, and correlated with all other voxels of the brain across animals. In the control group, the emerging correlative pattern was strongly overlapping for all three seed locations, indicating a uniform fronto-thalamo-hippocampal resting state network. In contrast, rTg4510 mice showed three distinct networks with minimal overlap. Frontal and thalamic networks were greatly diminished. The hippocampus, however, formed a new network with the whole parietal cortex. We conclude that resting-state functional networks are fragmented in the brain of rTg4510 mice. Thus, hypometabolism can be explained by reduced functional connectivity of brain areas devoid of tau-related pathology, such as the thalamus.

Differences in pre-treatment resting-state functional networks between responders and non-responders after one year of treatment with migraine monoclonal antibodies against calcitonin gene-related peptide

Differences in pre-treatment resting-state functional networks between responders and non-responders after one year of treatment with migraine monoclonal antibodies against calcitonin gene-related peptide

Association between gene expression and altered resting-state functional networks in type 2 diabetes

BackgroundType 2 diabetes (T2DM) is a polygenic metabolic disorder that accelerates brain aging and harms cognitive function. The underlying mechanism of T2DM-related brain functional changes has not been clarified.MethodsResting-fMRI data were obtained from 99 T2DM and 109 healthy controls (HCs). Resting-state functional connectivity networks (RSNs) were separated using the Independent Component Analysis (ICA) method, and functional connectivity (FC) differences between T2DM patients and HCs within the RSNs were detected. A partial least squares (PLS) regression was used to test the relation between gene expression from Allen Human Brain Atlas (AHBA) and intergroup FC differences within RSNs. Then the FC differences-related gene sets were enriched to determine the biological processes and pathways related to T2DM brain FC changes.ResultThe T2DM patients showed significantly increased FC in the left middle occipital gyrus (MOG) of the precuneus network (PCUN) and the right MOG / right precuneus of the dorsal attention network (DAN). FC differences within the PCUN were linked with the expression of genes enriched in the potassium channel and TrkB-Rac1 signaling pathways and biological processes related to synaptic function.ConclusionThis study linked FC and molecular alterations related to T2DM and suggested that the T2DM-related brain FC changes may have a genetic basis. This study hoped to provide a unique perspective to understand the biological substrates of T2DM-related brain changes.

Connectomics-based resting-state functional network alterations predict suicidality in major depressive disorder

Suicidal behavior is a major concern for patients who suffer from major depressive disorder (MDD). However, dynamic alterations and dysfunction of resting-state networks (RSNs) in MDD patients with suicidality have remained unclear. Thus, we investigated whether subjects with different severity of suicidal ideation and suicidal behavior may have different disturbances in brain RSNs and whether these changes could be used as the diagnostic biomarkers to discriminate MDD with or without suicidal ideation and suicidal behavior. Then a multicenter, cross-sectional study of 528 MDD patients with or without suicidality and 998 healthy controls was performed. We defined the probability of dying by the suicide of the suicidality components as a ‘suicidality gradient’. We constructed ten RSNs, including default mode (DMN), subcortical (SUB), ventral attention (VAN), and visual network (VIS). The network connections of RSNs were analyzed among MDD patients with different suicidality gradients and healthy controls using ANCOVA, chi-squared tests, and network-based statistical analysis. And support vector machine (SVM) model was designed to distinguish patients with mild-to-severe suicidal ideation, and suicidal behavior. We found the following abnormalities with increasing suicidality gradient in MDD patients: within-network connectivity values initially increased and then decreased, and one-versus-other network values decreased first and then increased. Besides, within- and between-network connectivity values of the various suicidality gradients are mainly negatively correlated with HAMD anxiety and positively correlated with weight. We found that VIS and DMN-VIS values were affected by age (p < 0.05), cingulo-opercular network, and SUB-VAN values were statistically influenced by sex (p < 0.05). Furthermore, the SVM model could distinguish MDD patients with different suicidality gradients (AUC range, 0.73–0.99). In conclusion, we have identified that disrupted brain connections were present in MDD patients with different suicidality gradient. These findings provided useful information about the pathophysiological mechanisms of MDD patients with suicidality.

Altered Large-Scale Resting-State Functional Network Connectivity in Convergence Insufficiency Young Adults Compared With Binocularly Normal Controls.

To investigate the underlying resting-state functional connectivity (RSFC) of symptomatic convergence insufficiency (CI) compared with binocularly normal controls (BNC) using functional magnetic resonance imaging (fMRI) under The Convergence Insufficiency Neuro‑mechanism Adult Population Study (NCT03593031). A total of 101 participants were eligible for this study. After removing datasets with motion artifacts, 49 CI and 47 BNC resting-state functional magnetic resonance imaging datasets were analyzed. CI was diagnosed with the following signs: (1) receded near point of convergence of 6 cm or greater, (2) decreased positive fusional vergence of less than 15∆ or failing Sheard's criteria of twice the near phoria, (3) near phoria of at least 4∆ more exophoric compared with the distance phoria, and (4) symptoms using the Convergence Insufficiency Symptom Survey (score of ≥21). RSFC was assessed using a group-level independent components analysis and dual regression. A behavioral correlation analysis using linear regression method was performed between clinical measures and RSFC using the significant difference between the CI and BNC. On average, a decreased RSFC was observed within the frontoparietal network, default mode network and visual network in patients with CI, compared with the participants with BNC (P < 0.05, corrected for multiple comparisons). The default mode network RSFC strength was significantly correlated with the PFV, near point of convergence, and difference between the horizontal phoria at near compared with far (P < 0.05). Results support altered RSFC in patients with CI compared with participants with BNC and suggest that these differences in underlying neurophysiology may in part be in connection with the differences in optometric visual function used to diagnose CI.