Functional Connectivity Strength Research Articles

Functional connectivity strength and topology differences in social phobia adolescents with and without ADHD comorbidity

Social phobia (SP) is associated with changes in functional connectivity strength and topology. However, reported changes have been heterogeneous due to small sample sizes, inconsistent methodologies, and comorbidities, such as attention-deficit/hyperactivity disorder (ADHD), which has a high comorbidity rate with SP. Furthermore, there are few studies looking at SP in an adolescent population, a critical period for the development of the social brain. This project focuses on functional connectivity strength and topological differences in social phobia patients with and without ADHD comorbidity. We examined resting-state functional MRI images from 158 subjects, including 36 SP participants without ADHD comorbidity, 60 SP participants with ADHD comorbidity, and 62 healthy controls, with an overall average age of 14.16. We used a data-driven approach to examine impaired functional connectivity in a whole-brain analysis and higher-order topological differences in functional brain networks. We identified changes in the cerebellum and default mode network in social phobia patients as a whole, with the presence of ADHD comorbidity affecting various subsystems of the default mode network. Social phobia functional connectivity networks resembled random graphs, and local connectivity patterns in the superior occipital gyrus were different due to ADHD comorbidity. These alterations may indicate impairments in self-related processing, imagery, mentalizing, and predictive processes. We then used these changes in a linear support vector machine to distinguish between each pair of groups and achieved prediction accuracy significantly above chance rates. Our study extends prior research by showing that functional connectivity changes exist at adolescence, which are affected by ADHD comorbidity. As such, these results offer a new perspective in examining neurobiological changes in SP patients.

Altered Functional Connectivity of Basal Ganglia in Mild Cognitive Impairment and Alzheimer's Disease.

(1) Background: Alzheimer's disease (AD), an age-progressive neurodegenerative disease that affects cognitive function, causes changes in the functional connectivity of the default-mode network (DMN). However, the question of whether AD-related changes occur in the functional connectivity of the basal ganglia has rarely been specifically analyzed. This study aimed to measure the changes in basal ganglia functional connectivity among patients with AD and mild cognitive impairment (MCI) in their resting state using the functional connectivity density (FCD) value, the functional connectivity (FC) intensity, and the graph theory index, and to confirm their influence on clinical manifestations. (2) Methods: Resting-state functional MRI (rs-fMRI) and neuropsychological data from 48 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used for analyses. The 48 ADNI participants comprised 16 patients with AD, 16 patients with MCI, and 16 normal controls (NCs). The functional connectivity of basal ganglia was evaluated by FCDs, FC strength, and graph theory index. We compared voxel-based FCD values between groups to show specific regions with significant variation and significant connectivity from ROI conduction to ROI analysis. Pearson's correlation analyses between functional connectivity and several simultaneous clinical variables were also conducted. Additionally, receiver operating characteristic (ROC) analyses associated with classification were conducted for both FCD values and graph theory indices. (3) Results: The level of FCD in patients with cognitive impairment showed obvious abnormalities (including short-range and long-range FCD). In addition to DMN-related regions, aberrant functional connectivity was also found to be present in the basal ganglia, especially in the caudate and amygdala. The FCD values of the basal ganglia (involving the caudate and amygdala) were closely related to scores from the Mini-Mental State Examination (MMSE) and the Functional Activities Questionnaire (FAQ); meanwhile, the graph theory indices (involving global efficiency and degree) of the basal ganglia (involving the caudate, amygdala, and putamen) were also found to be closely correlated with MMSE scores. In ROC analyses of both FCD and graph theory, the amygdala was of the utmost importance in the early-stage detection of MCI; additionally, the caudate nucleus was found to be crucial in the progression of cognitive decline and AD diagnosis. (4) Conclusions: It was systematically confirmed that there is a phenomenon of change in the functional connections in the basal ganglia during cognitive decline. The findings of this study could improve our understanding of AD and MCI pathology in the basal ganglia and make it possible to propose new targets for AD treatment in further studies.

Altered hippocampal functional connectivity after the rupture of anterior communicating artery aneurysm.

Aneurysmal subarachnoid hemorrhage (SAH) predisposes hippocampal injury, a major cause of follow-up cognitive impairment. Our previous study has revealed an abnormal resting-state brain network in patients after the rupture of anterior communicating artery (ACoA) aneurysm. However, the functional connectivity (FC) characteristics of the hippocampus and its relationship with cognitive performance in these patients remain unknown. This study ultimately included 26 patients and 19 age- and sex-matched controls who completed quality control for resting-state functional magnetic resonance imaging (fMRI). The mean time series for each side of the hippocampus was extracted from individuals and then a seed-to-voxel analysis was performed. We compared the difference in FC strength between the two groups and subsequently analyzed the correlations between abnormal FC and their cognitive performance. The results of bilateral hippocampus-based FC analysis were largely consistent. Compared with the healthy controls, patients after the rupture of ACoA aneurysm exhibited significantly decreased FC between the hippocampus and other brain structures within the Papez circuit, including bilateral anterior and middle cingulate cortex (MCC), bilateral medial superior frontal gyrus, and left inferior temporal gyrus (ITG). Instead, increased FC between the hippocampus and bilateral insula was observed. Correlation analyses showed that more subjective memory complaints or lower total cognitive scores were associated with decreased connectivity in the hippocampus and several brain regions such as left anterior cingulate cortex (ACC) and frontotemporal cortex. These results extend our previous findings and suggest that patients with ruptured ACoA aneurysm exist hypoconnectivity between the hippocampus and multiple brain regions within the Papez circuit. Deactivation of the Papez circuit may be a crucial neural mechanism related to cognitive deficits in patients after the rupture of ACoA aneurysm.

Limbic pathway vulnerability associates with neurologic outcome in children after cardiac arrest

AimTo analyze whether brain connectivity sequences including diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rsfMRI) identify vulnerable brain regions and networks associated with neurologic outcome after pediatric cardiac arrest. MethodsChildren aged 2 d-17 y with cardiac arrest were enrolled in one of 2 parent studies at a single center. Clinically indicated brain MRI with DTI and rsfMRI and performed within 2 weeks after arrest were analyzed. Tract-wise fractional anisotropy (FA) and axial, radial, and mean diffusivity assessed DTI, and functional connectivity strength (FCS) assessed rsfMRI between outcome groups. Unfavorable neurologic outcome was defined as Pediatric Cerebral Performance Category score 4–6 or change > 1 between 6 months after arrest vs baseline. ResultsAmong children with DTI (n = 28), 57% had unfavorable outcome. Mean, radial, axial diffusivity and FA of varying direction of magnitude in the limbic tracts, including the right cingulum parolfactory, left cingulum parahippocampal, corpus callosum forceps major, and corpus callosum forceps minor tracts, were associated with unfavorable neurologic outcome (p < 0.05). Among children with rsfMRI (n = 12), 67% had unfavorable outcome. Decreased FCS in the ventromedial and dorsolateral prefrontal cortex, insula, precentral gyrus, anterior cingulate, and inferior parietal lobule were correlated regionally with unfavorable neurologic outcome (p < 0.05 Family-Wise Error corrected). ConclusionDecreased multimodal connectivity measures of paralimbic tracts were associated with unfavorable neurologic outcome after pediatric cardiac arrest. Longitudinal analysis correlating brain connectivity sequences with long term neuropsychological outcomes to identify the impact of pediatric cardiac arrest in vulnerable brain networks over time appears warranted.

Neural Basis of the Implicit Learning of Complex Artificial Grammar with Nonadjacent Dependencies.

The capacity for the implicit learning/processing of complex grammar with nonadjacent dependencies is an important feature of human language learning. In this fMRI study, using an implicit AGL paradigm, we explored the neural basis of the implicit learning of the nonadjacent dependency rule, disentangling from sequence-based chunk knowledge (i.e., local sequential regularities or substring) by focusing on the low chunk strength items (which were naturally less similar to training strings), based on tracking neural responses during training and test phases. After listening to and memorizing a series of strings of 10 syllables generated from nonadjacent artificial grammar in the training phase, participants implicitly acquired the knowledge of grammar and chunks. Regarding grammaticality, Broca's area was specifically related to low chunk strength grammatical strings relative to nongrammatical strings in the test phase. This region showed decreased activity with time in the training phase, and a lesser decrease in activity was associated with higher performance in grammar learning. Furthermore, Broca's area showed significantly higher strength of functional connectivity with the left superior temporal gyrus in the low chunk strength grammatical string compared with nongrammatical strings, and this functional connectivity increased with the training time. For the chunks, the performance of accurate discrimination of high chunk strength from low chunk strength nongrammatical strings was predicted by hippocampal activity in the training phase. Converging evidence from the training and test phases showed that Broca's area and its functional connectivity with the left superior temporal gyrus were engaged in the implicit learning/processing of the nonadjacent dependency rule, separating the effects of chunks.

Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study.

The purpose of this study was to investigate the dynamic functional network connectivity (FNC) and its relationship with cognitive function in obstructive sleep apnea (OSA) patients from normal cognition (OSA-NC) to mild cognitive impairment (OSA-MCI). Eighty-two male OSA patients and 48 male healthy controls (HC) were included in this study. OSA patients were classified to OSA-MCI (n = 41) and OSA-NC (n = 41) based on cognitive assessments. The independent component analysis was used to determine resting-state functional networks. Then, a sliding-window approach was used to construct the dynamic FNC, and differences in temporal properties of dynamic FNC and functional connectivity strength were compared between OSA patients and the HC. Furthermore, the relationship between temporal properties and clinical assessments were analyzed in OSA patients. Two different connectivity states were identified, namely, State I with stronger connectivity and lower frequency, and State II with lower connectivity and relatively higher frequency. Compared to HC, OSA patients had a longer mean dwell time and higher fractional window in stronger connectivity State I, and opposite result were found in State II, which was mainly reflected in OSA-MCI patients. The number of transitions was an increasing trend and positively correlated with cognitive assessment in OSA-MCI patients. Compared with HC, OSA patients showed extensive abnormal functional connectivity in stronger connected State I and less reduced functional connectivity in lower connected State II, which were mainly located in the salience network, default mode network, and executive control network. Our study found that OSA patients showed abnormal dynamic FNC properties, which was a continuous trend from HC, and OSA-NC to OSA-MCI, and OSA patients showed abnormal dynamic functional connectivity strength. The number of transformations was associated with cognitive impairment in OSA-MCI patients, which may provide new insights into the neural mechanisms in OSA patients.

Problematic smartphone use is associated with differences in static and dynamic brain functional connectivity in young adults.

This study aimed to investigate the possible associations between problematic smartphone use and brain functions in terms of both static and dynamic functional connectivity patterns. Resting-state functional magnetic resonance imaging data were scanned from 53 young healthy adults, all of whom completed the Short Version of the Smartphone Addiction Scale (SAS-SV) to assess their problematic smartphone use severity. Both static and dynamic functional brain network measures were evaluated for each participant. The brain network measures were correlated the SAS-SV scores, and compared between participants with and without a problematic smartphone use after adjusting for sex, age, education, and head motion. Two participants were excluded because of excessive head motion, and 56.9% (29/51) of the final analyzed participants were found to have a problematic smartphone use (SAS-SV scores ≥ 31 for males and ≥ 33 for females, as proposed in prior research). At the global network level, the SAS-SV score was found to be significantly positively correlated with the global efficiency and local efficiency of static brain networks, and negatively correlated with the temporal variability using the dynamic brain network model. Large-scale subnetwork analyses indicated that a higher SAS-SV score was significantly associated with higher strengths of static functional connectivity within the frontoparietal and cinguloopercular subnetworks, as well as a lower temporal variability of dynamic functional connectivity patterns within the attention subnetwork. However, no significant differences were found when directly comparing between the groups of participants with and without a problematic smartphone use. Our results suggested that problematic smartphone use is associated with differences in both the static and dynamic brain network organizations in young adults. These findings may help to identify at-risk population for smartphone addiction and guide targeted interventions for further research. Nevertheless, it might be necessary to confirm our findings in a larger sample, and to investigate if a more applicable SAS-SV cutoff point is required for defining problematic smartphone use in young Chinese adults nowadays.

Abnormal Properties of Cortical Functional Brain Network in Major Depressive Disorder: Graph Theory Analysis Based on Electroencephalography-Source Estimates

Studies of scalp electroencephalography (EEG) had shown altered topological organization of functional brain networks in patients with major depressive disorder (MDD). However, most previous EEG-based network analyses were performed at sensor level, while the interpretation of obtained results was not straightforward due to volume conduction effect. To reduce the impact of this defect, the whole cortical functional brain networks of MDD patients were studied during resting state based on EEG-source estimates in this paper. First, scalp EEG signals were recorded from 19 patients with MDD and 20 normal controls under resting eyes-closed state, and cortical neural signals were estimated by using sLORETA method. Then, the correntropy coefficient of wavelet packet coefficients was performed to calculate functional connectivity (FC) matrices in four different frequency bands: δ, θ, α, β, respectively. Afterwards, topological properties of brain networks were analyzed by graph theory approaches. The results showed that the global FC strength of MDD patients was significantly higher than that of healthy subjects in α band. Also, it was found that MDD patients have abnormally increased clustering coefficient and local efficiency in both α and β bands compared to normal people. Furthermore, patients with MDD exhibited increased nodal clustering coefficients in the left lingual gryus and left precuneus in α band. In addition, β band global clustering coefficient was positively correlated with the scores of depression severity. Therefore, the findings indicated the cortical functional brain networks in MDD patients were disruptions, which suggested it would be one of potential causes of depression.

Functional brain network and trail making test changes following major surgery and postoperative delirium: a prospective, multicentre, observational cohort study

BackgroundDelirium is a frequent complication after surgery in older adults and is associated with an increased risk of long-term cognitive impairment and dementia. Disturbances in functional brain networks were previously reported during delirium. We hypothesised that alterations in functional brain networks persist after remission of postoperative delirium and that functional brain network alterations are associated with long-term cognitive impairment. MethodsIn this prospective, multicentre, observational cohort study, we included older patients who underwent clinical assessments (including the Trail Making Test B [TMT-B]) and resting-state functional MRI (rs-fMRI) before and 3 months after elective surgery. Delirium was assessed on the first seven postoperative days. ResultsOf the 554 enrolled patients, 246 remained after strict motion correction, of whom 38 (16%) developed postoperative delirium. The rs-fMRI functional connectivity strength increased 3 months after surgery in the total study population (β=0.006; 95% confidence interval [CI]: 0.001–0.011; P=0.013), but it decreased after postoperative delirium (β=–0.015; 95% CI: –0.028 to 0.002; P=0.023). No difference in TMT-B scores was found at follow-up between patients with and without postoperative delirium. Patients with decreased functional connectivity strength declined in TMT-B scores compared with those who did not (β=11.04; 95% CI: 0.85–21.2; P=0.034). ConclusionsPostoperative delirium was associated with decreased brain functional connectivity strength after 3 months, suggesting that delirium has a long-lasting impact on brain networks. The decreased connectivity strength was associated with significant cognitive deterioration after major surgery. Clinical trial registrationNCT02265263.

In Vivo Tau Burden Is Associated with Abnormal Brain Functional Connectivity in Alzheimer's Disease: A 18F-Florzolotau Study.

Purpose: 18F-Florzolotau is a novel second-generation tau radiotracer that shows higher binding affinity and selectivity and no off-target binding. The proportion loss of functional connectivity strength (PLFCS) is a new indicator for representing brain functional connectivity (FC) alteration. This study aims to estimate the relationship between the regional tau accumulation and brain FC abnormality in Alzheimer’s disease (AD) and mild cognitive impairment (MCI) patients based on Florzolotau PET and fMRI. Methods: 22 NC (normal control), 31 MCI and 42 AD patients who have already been scanned with 18F-Florzolotau PET were recruited in this study. (We calculated the PLFCS and standardized uptake value ratio (SUVR) of each node based on the Brainnetome atlas (BNA) template. The SUVR of 246 brain regions was calculated with the cerebellum as the reference region. Further functional connection strength (FCs), PLFCS and SUVR of each brain region were obtained in three groups for comparison.) For each patient, PLFCS and standardized uptake value ratio (SUVR) were calculated based on the Brainnetome atlas (BNA) template. These results, as well as functional connection strength (FCs), were then compared between different groups. Multiple permutation tests were used to determine the target nodes between NC and cognitive impairment (CI) groups (MCI and AD). The relationship between PLFCS and neuropsychological scores or cortical tau deposit was investigated via Pearson correlation analysis. Results: Higher PLFCS and FCs in AD and MCI groups were found compared to the NC group. The PLFCS of 129 brain regions were found to be different between NC and CI groups, and 8 of them were correlated with tau SUVR, including superior parietal lobule (MCI: r = 0.4360, p = 0.0260, AD: r = −0.3663, p = 0.0280), middle frontal gyrus (AD: MFG_R_7_2: r = 0.4106, p = 0.0129; MFG_R_7_5: r = 0.4239, p = 0.0100), inferior frontal gyrus (AD: IFG_R_6_2: r = 0.3589, p = 0.0316), precentral gyrus (AD: PrG_R_6_6: r = 0.3493, p = 0.0368), insular gyrus (AD: INS_R_6_3: r = 0.3496, p = 0.0366) and lateral occipital cortex (AD: LOcC _L_4_3: r = −0.3433, p = 0.0404). Noteworthily, the opposing relationship was found in the superior parietal lobule in the MCI and AD groups. Conclusions: Brain functional connectivity abnormality is correlated with tau pathology in AD and MCI.

Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life.

Structural connectome constrained graphical lasso for MEG partial coherence.

Structural connectivity provides the backbone for communication between neural populations. Since axonal transmission occurs on a millisecond time scale, measures of M/EEG functional connectivity sensitive to phase synchronization, such as coherence, are expected to reflect structural connectivity. We develop a model of MEG functional connectivity whose edges are constrained by the structural connectome. The edge strengths are defined by partial coherence, a measure of conditional dependence. We build a new method-the adaptive graphical lasso (AGL)-to fit the partial coherence to perform inference on the hypothesis that the structural connectome is reflected in MEG functional connectivity. In simulations, we demonstrate that the structural connectivity's influence on the partial coherence can be inferred using the AGL. Further, we show that fitting the partial coherence is superior to alternative methods at recovering the structural connectome, even after the source localization estimates required to map MEG from sensors to the cortex. Finally, we show how partial coherence can be used to explore how distinct parts of the structural connectome contribute to MEG functional connectivity in different frequency bands. Partial coherence offers better estimates of the strength of direct functional connections and consequently a potentially better estimate of network structure.

Investigating the mechanism and prognosis of patients with disorders of consciousness on the basis of brain networks between the thalamus and whole-brain.

PurposeThis study aimed to investigate the changes in the functional connectivity between the bilateral thalamus and the whole-brain in patients with severe traumatic brain injury (sTBI) patients suffering from disorders of consciousness (DOC) and to explore their potential prognostic representation capacity.MethodsThe sTBI patients suffering from DOC and healthy controls underwent functional magnetic resonance imaging. We defined patients with the Extended Glasgow Outcome Score (GOS-E) ≥ 3 as the wake group and GOS-E = 2 as the coma group. The differences in functional connectivity between sTBI and healthy controls and between wake and coma groups were compared. Based on the brain regions with altered functional connectivity between wake and coma groups, they were divided into 26 regions of interest. Based on the Z-values of regions of interest, the receiver operating characteristic analysis was conducted to classify the prognosis of patients.ResultsA total of 28 patients and 15 healthy controls were finally included. Patients who had DOC indicated a significant disruption of functional connectivity between the bilateral thalamus and the whole-brain (FDR corrected, P < 0.0007). The functional connectivity strength (bilateral thalamus to whole-brain) was significantly different between coma patients who went on to wake and those who were eventually non-awake at 6 months after sTBI (Alphasim corrected, P < 0.05). Furthermore, the 26 regions of interest had a similar or even better prognostic distinction ability than the admission Glasgow coma score.ConclusionThe thalamus-based system of consciousness of sTBI patients suffering from DOC is disrupted. There are differences in the thalamus-to-whole-brain network between wake and coma groups and these differences have potential prognostic characterization capability.

Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder.

Treatment non-response and recurrence are the main sources of disease burden in major depressive disorder (MDD). However, little is known about its neurobiological mechanism concerning the brain network changes accompanying pharmacotherapy. The present study investigated the changes in the intrinsic brain networks during 6-month antidepressant treatment phase associated with the treatment response and recurrence in MDD. Resting-state functional magnetic resonance imaging was acquired from untreated patients with MDD and healthy controls at baseline. The patients' depressive symptoms were monitored by using the Hamilton Rating Scale for Depression (HAMD). After 6 months of antidepressant treatment, patients were re-scanned and followed up every 6 months over 2 years. Traditional statistical analysis as well as machine learning approaches were conducted to investigate the longitudinal changes in macro-scale resting-state functional network connectivity (rsFNC) strength and micro-scale resting-state functional connectivity (rsFC) associated with long-term treatment outcome in MDD. Repeated measures of the general linear model demonstrated a significant difference in the default mode network (DMN) rsFNC change before and after the 6-month antidepressant treatment between remitters and non-remitters. The difference in the rsFNC change over the 6-month antidepressant treatment between recurring and stable MDD was also specific to DMN. Machine learning analysis results revealed that only the DMN rsFC change successfully distinguished non-remitters from the remitters at 6 months and recurring from stable MDD during the 2-year follow-up. Our findings demonstrated that the intrinsic DMN connectivity could be a unique and important target for treatment and recurrence prevention in MDD.

Impaired Neurovascular Function Underlies Poor Neurocognitive Outcomes and Is Associated with Nitric Oxide Bioavailability in Congenital Heart Disease.

We use a non-invasive MRI proxy of neurovascular function (pnvf) to assess the ability of the vasculature to supply baseline metabolic demand, to compare pediatric and young adult congenital heart disease (CHD) patients to normal referents and relate the proxy to neurocognitive outcomes and nitric oxide bioavailability. In a prospective single-center study, resting-state blood-oxygen-level-dependent (BOLD) and arterial spin labeling (ASL) MRI scans were successfully obtained from 24 CHD patients (age = 15.4 ± 4.06 years) and 63 normal referents (age = 14.1 ± 3.49) years. Pnvf was computed on a voxelwise basis as the negative of the ratio of functional connectivity strength (FCS) estimated from the resting-state BOLD acquisition to regional cerebral blood flow (rCBF) as estimated from the ASL acquisition. Pnvf was used to predict end-tidal CO2 (PETCO2) levels and compared to those estimated from the BOLD data. Nitric oxide availability was obtained via nasal measurements (nNO). Pnvf was compared on a voxelwise basis between CHD patients and normal referents and correlated with nitric oxide availability and neurocognitive outcomes as assessed via the NIH Toolbox. Pnvf was shown as highly predictive of PETCO2 using theoretical modeling. Pnvf was found to be significantly reduced in CHD patients in default mode network (DMN, comprising the ventromedial prefrontal cortex and posterior cingulate/precuneus), salience network (SN, comprising the insula and dorsal anterior cingulate), and central executive network (CEN, comprising posterior parietal and dorsolateral prefrontal cortex) regions with similar findings noted in single cardiac ventricle patients. Positive correlations of Pnvf in these brain regions, as well as the hippocampus, were found with neurocognitive outcomes. Similarly, positive correlations between Pnvf and nitric oxide availability were found in frontal DMN and CEN regions, with particularly strong correlations in subcortical regions (putamen). Reduced Pnvf in CHD patients was found to be mediated by nNO. Mediation analyses further supported that reduced Pnvf in these regions underlies worse neurocognitive outcome in CHD patients and is associated with nitric oxide bioavailability. Impaired neuro-vascular function, which may be non-invasively estimated via combined arterial-spin label and BOLD MR imaging, is a nitric oxide bioavailability dependent factor implicated in adverse neurocognitive outcomes in pediatric and young adult CHD.

Automated Creativity Prediction Using Natural Language Processing and Resting-State Functional Connectivity: An fNIRS Study

ABSTRACT Evidence from fMRI research indicates that individual creative thinking ability – defined as performance on divergent thinking tasks, subjectively assessed by human raters – can be predicted based on the strength of functional connectivity (FC) between the brain’s default mode network (DMN) and frontoparietal control network (FPCN). Here, we sought to replicate and extend these findings in two ways: 1) using a natural language processing method to objectively quantify creative performance (instead of subjective human ratings), and 2) employing functional near-infrared spectroscopy (fNIRS), a neuroimaging method that allows measuring brain activity in more naturalistic settings (compared to fMRI). By applying elastic-net regression to resting-state functional connectivity data, we constructed two separate prediction models to predict participants’ creative performance based on static FC and dynamic FC respectively. Results from the static network analysis indicated that fNIRS-functional connectivity between the DMN and FPCN can reliably predict creative ability (assessed objectively via natural language processing; R2 = .38). Moreover, we show that dynamic DMN-FPCN functional connectivity predicts creative ability nearly twice as strong as static connectivity (R2 = .67). Our work demonstrates that objective measures of creativity can be predicted from resting-state functional connectivity and that the procedure can be efficiently implemented within highly naturalistic settings with fNIRS.

The role of basal ganglia network in neural plasticity in neuromyelitis optica spectrum disorder with myelitis

ObjectivesTo explore the alternation of the brain baseline activity in neuromyelitis optica spectrum disorder (NMOSD) patients after myelitis, and characterize the representation of the neural plasticity process. MethodsClinical evaluation and resting-state fMRI were obtained from 20 NMOSD patients with myelitis and 20 healthy controls, matched in gender and age. Resting-state networks (RSNs) were identified through independent component analysis (ICA), and functional connectivity (FC) intra-RSNs and between region-of-interest (ROI) seed to whole-brain voxels were analyzed. Between-group comparisons and correlations with motor performance were also assessed. ResultsA total of 14 main functional RSNs were identified. Group comparison of intra-network FCs revealed that FC strengths increased in basal ganglia network (BGN) and left frontoparietal network, decreased in sensorimotor network and default mode network in NMOSD. Better motor performance was found closely correlated with higher FC of BGN. Additionally, remarkably increased FC between caudate in BGN with cerebellum, frontal lobe and parietal lobe was discovered in further ROI-based whole-brain voxels FC analysis. ConclusionsNMOSD patients presented wide brain resting-state functional connectivity alterations after myelitis, and BGN might be highly active in the process of neural plasticity in chronic stage of NMOSD. Besides, understanding neural plasticity representation, especially that in NMOSD patients after myelitis, might have important applications in monitoring and designing rehabilitative approaches.

The learning-relative hemodynamic modulation of cortical plasticity induced by a force-control motor training.

BackgroundNovel motor skills are generally acquired through repetitive practices which are believed to be strongly related to neural plasticity mechanisms. This study aimed to investigate the learning-relative hemodynamic modulation of cortical plasticity induced by long-term motor training.MethodsAn 8-day participation-control program was conducted. Eighteen right-handed healthy participants were recruited and randomly assigned into the training (12) and control groups (6). The training group were arranged to undergo the 8-day block-designed motor training which required to repeat a visuomotor force-control task. The functional near-infrared spectroscopy (fNIRS) was used to continuously monitor the cortical hemodynamic response during training. Two transcranial magnetic stimulation (TMS) measurements were performed before and after training to evaluate the cortical excitability changes. The transfer effects of learning were also investigated.ResultsThe behavior performance was quantified via score execution accuracy to illustrate the fast/slow learning stages as experience cumulated. The cortical hemodynamic activations mapped by fNIRS exhibited a temporal evolution trends that agreed the expansion–renormalization model, which assumed the brain modulation against skill acquisition includes complex mechanisms of neural expansion, selection, and renormalization. Functional connectivity (FC) analysis showed the FC strength was maintained, while the measured homodynamic activation returned to baseline after certain level of skill acquisition. Furthermore, the TMS results demonstrated a significant increase of motor evoked potential (MEP) on the targeted muscle for the trained participants, who significantly outperformed the untrained subjects in learning transfer investigation.ConclusionThe study illustrated the expansion–renormalization trends during continuous motor training, and relative analysis showed the functional connectivity enhancement may be maintained after amplitude renormalization of cortical hemodynamic activations. The TMS findings further gave an implication of neural facilitations on the descending motor pathway when brain activation returned to renormalization status after certain level of learning stages was achieved, and the learning can transfer to enhance the performance while encountering similar tasks.

Association between Long-Term Air Pollution, Chronic Traffic Noise, and Resting-State Functional Connectivity in the 1000BRAINS Study.

Background:Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown.Objective:This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks.Methods:Data from 574 participants (44.1% female, 56–85 years of age) in the German 1000BRAINS study (2011–2015) were analyzed. Exposure to particulate matter (, , and absorbance), accumulation mode particle number (), and nitrogen dioxide () was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h () and nighttime () means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables.Results:Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, (95% CI: , 0.009) per 0.3 increase in absorbance and (95% CI: , ) per 1-y age increase].Conclusion:High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737

Moxibustion for primary dysmenorrhea: A resting-state functional magnetic resonance imaging study exploring the alteration of functional connectivity strength and functional connectivity.

IntroductionPrimary dysmenorrhea (PDM) is a common gynecological disease and chronic pain disorder. Moxibustion, a form of traditional Chinese medicine therapy, has proven to be effective for PDM. However, the central mechanisms of PDM and moxibustion for PDM are still unclear. This study aims to explore the potential central mechanism of PDM and clarify the possible mechanism of moxibustion for relieving pain.Materials and methodsA total of 23 PDM patients and 23 matched healthy controls (HCs) were enrolled. For PDM patients, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected pre- and post-moxibustion treatment of 3 consecutive menstrual cycles, respectively. For HCs, rs-fMRI data were collected in the baseline. The resting-state functional connectivity strength (rs-FCS) analysis and the resting-state functional connectivity (rs-FC) analysis based on the region of interest (ROI) were combined to be conducted.ResultsCompared to HCs, PDM patients showed weaker rs-FCS in the left inferior frontal gyrus (IFG). After the moxibustion treatment, rs-FCS in the left IFG was increased with clinical improvement. Then, the left IFG was chosen as ROI, and the rs-FC analysis was conducted. It showed that the left IFG rs-FC in the bilateral anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), the left posterior cingulate cortex (PCC)/precuneus (PCU), and the left parahippocampal gyrus (PHG) decreased after moxibustion treatment, most of which belong to the default mode network (DMN).ConclusionOur results highlight the role of the left IFG and the DMN in PDM. Specifically, the central mechanism of moxibustion for analgesia may be related to modulating the disorders of the reappraisal and processing of pain stimuli through influencing the cognition of pain.