Exploring the bidirectional relationships between MRI resting-state functional connectivity networks and cardiovascular diseases: a Mendelian randomization study

Introduction: Even with the increased access and early initiation of combination antiretroviral therapy, children with perinatally acquired human immunodeficiency virus (CPHIV) continue to demonstrate white matter alterations. Children perinatally HIV-exposed, but uninfected (CHEU) alike show differences in white matter integrity compared with children who are HIV-unexposed and uninfected (CHUU). Objectives: Mapping white matter connections that link gray matter regions that form resting-state (RS) functional networks may demonstrate whether structural and functional connectivity alterations in HIV infection and exposure may be related. We hypothesized reduced structural connectivity in CPHIV within the default mode network (DMN), visual, ventral DMN (vDMN), somatosensory, salience, auditory, motor, executive, basal ganglia, and posterior DMN (pDMN). We also hypothesized that CHEU will have increased structural connectivity compared with CHUU in the vDMN, somatosensory, pDMN, dorsal attention, salience, auditory, motor and basal ganglia. Methods: Study participants were 61 seven-year-old CPHIV and 46 age-matched children who are HIV uninfected (CHU) (19 CHEU). We used diffusion tensor imaging-based tractography to investigate white matter connections that link gray matter regions within RS functional networks. Results: We found altered white matter integrity in the somatosensory, salience, default mode, and motor networks of CPHIV compared with CHU. The superior temporal cortex, superior frontal cortex, and putamen were affected in all four networks and have also been reported to demonstrate morphological alterations in the same cohort. In CHEU, white matter integrity was higher in the visual network, pDMN, and motor network compared with CHUU. Conclusion: Our results suggest that altered white matter integrity may influence gray matter morphology and functional network alterations. Impact statement The long-term effects of human immunodeficiency virus (HIV) and exposure on the developing brain in the combination antiretroviral therapy era are still not well known. We use diffusion tensor imaging-based tractography to explore these effects on white matter connections that link gray matter regions within functional networks. Our findings provide a context for HIV-associated white matter and connectivity abnormalities.

Learning new motor skills is a fundamental process that involves the sequencing of actions. Skill develops with practice and time and manifests as performance that is fast and accurate. Although we know that learning can occur through an implicit process in the absence of conscious awareness, and across multiple temporal scales, the precise neural mechanisms mediating implicit motor sequence learning remain poorly understood. Similarly the capacity for interventions with known influence on learning and memory, such as cardiovascular exercise, to facilitate implicit learning is yet to be clearly established. Here we investigated the neuroplasticity of implicit motor sequence learning and the effect of acute exercise priming. Healthy adults (39.5% female) aged 22.55 ± 2.69 years were allocated to either a high-intensity interval training (HIIT) exercise group (n=16) or to a very low-intensity control group (n=17). After exercise participants performed a serial reaction time task, magnetic resonance (MR) spectroscopy estimates of sensorimotor GABA were acquired before and after exercise and during task performance, and resting-state functional magnetic resonance imaging (fMRI) was acquired at the end of the protocol. We show that early stages of learning are linked to default mode network connectivity, whereas the overall degree of learning following sustained practice is associated with motor network connectivity. Sensorimotor GABA concentration was linked to the early stages of learning, and GABA concentration was modulated following HIIT, although the two were not related. Overall through the integration of multiple neuroimaging modalities we demonstrate that interactions between hippocampal and motor networks underlie implicit motor sequence learning. KEY POINTS: Motor learning occurs across different temporal scales and can arise implicitly in the absence of conscious awareness. Explicit motor learning is linked to the brain's primary inhibitory neurotransmitter, GABA and interactions across motor and hippocampal networks. Whether these same neural mechanisms are implicated in implicit learning is unclear. Similarly the capacity to influence implicit learning via priming with cardiovascular exercise is yet to be clearly established. We show that early implicit learning is underpinned by default mode network connectivity and sensorimotor GABA concentration, whereas total learning following sustained practice is linked to motor network connectivity. We also found that high-intensity interval training (HIIT) exercise elevated sensorimotor GABA concentration, but not the magnitude of implicit learning. Overall our results highlight shared involvement of default mode and motor networks in implicit motor sequence learning.

Posterior cortical atrophy and logopenic progressive aphasia are atypical clinical presentations of Alzheimer's disease. Resting-state functional connectivity studies have shown functional network disruptions in both phenotypes, particularly involving the language network in logopenic progressive aphasia and the visual network in posterior cortical atrophy. However, little is known about how connectivity differs both within and between brain networks in these atypical Alzheimer's disease phenotypes. A cohort of 144 patients was recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, USA, and underwent structural and resting-state functional MRI. Spatially preprocessed data were analysed to explore the default mode network and the salience, sensorimotor, language, visual and memory networks. The data were analysed at the voxel and network levels. Bayesian hierarchical linear models adjusted for age and sex were used to analyse within- and between-network connectivity. Reduced within-network connectivity was observed in the language network in both phenotypes, with stronger evidence of reductions in logopenic progressive aphasia compared to controls. Only posterior cortical atrophy showed reduced within-network connectivity in the visual network compared to controls. Both phenotypes showed reduced within-network connectivity in the default mode and sensorimotor networks. No significant change was noted in the memory network, but a slight increase in the salience within-network connectivity was seen in both phenotypes compared to controls. Between-network analysis in posterior cortical atrophy showed evidence of reduced visual-to-language network connectivity, with reduced visual-to-salience network connectivity, compared to controls. An increase in visual-to-default mode network connectivity was noted in posterior cortical atrophy compared to controls. Between-network analysis in logopenic progressive aphasia showed evidence of reduced language-to-visual network connectivity and an increase in language-to-salience network connectivity compared to controls. Findings from the voxel-level and network-level analysis were in line with the Bayesian hierarchical linear model analysis, showing reduced connectivity in the dominant network based on diagnosis and more crosstalk between networks in general compared to controls. The atypical Alzheimer's disease phenotypes were associated with disruptions in connectivity, both within and between brain networks. Phenotype-specific differences in connectivity patterns were noted in the visual network for posterior cortical atrophy and the language network for logopenic progressive aphasia.

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.

Learning new motor skills is a fundamental process that involves the sequencing of actions. Skill develops with practice and time, and manifests as performance that is fast and accurate. Although we know that learning can occur through animplicitprocess in the absence of conscious awareness, and across multiple temporal scales, the precise neural mechanisms mediating implicit motor sequence learning remain poorly understood. Similarly, the capacity for interventions with known influence on learning and memory, such as cardiovascular exercise, to facilitate implicit learning is yet to be clearly established. Here, we investigated the neuroplasticity of implicit motor sequence learning and the effect of acute exercise priming. Healthy adults (39.5% female) aged 22.55 ± 2.69 years were allocated to either a high-intensity exercise (HIIT) group (n = 16) or to a very low-intensity control group (n = 17). Following exercise, participants performed a serial reaction time task. MR spectroscopy estimates of sensorimotor gamma-aminobutyric acid (GABA) were acquired before and after exercise, and during task performance, and resting-state fMRI was acquired at the end of the protocol. We show that early stages of learning are linked to default mode network connectivity, while the overall degree of learning following sustained practice is associated with motor network connectivity. Sensorimotor GABA concentration was linked to the early stages of learning, and GABA concentration was modulated following HIIT, although the two were not related. Overall, via integration of multiple neuroimaging modalities we demonstrate that interactions between hippocampal and motor networks underlieimplicitmotor sequence learning.Key points summary-Motor learning occurs across different temporal scales and can arise implicitly in the absence of conscious awareness.-Explicitmotor learning is linked to the brain’s primary inhibitory neurotransmitter, GABA, and interactions across motor and hippocampal networks.-Whether these same neural mechanisms are implicated inimplicitlearning is unclear. Similarly, the capacity to influence learning via priming with cardiovascular exercise is yet to be clearly established.-We show that early implicit learning is underpinned by default mode network connectivity and sensorimotor GABA concentration, while total learning following sustained practice is linked to motor network connectivity. We also found that HIIT exercise elevated sensorimotor GABA concentration, but not the magnitude of implicit learning.-Overall, our results highlight shared involvement of default mode and motor networks in implicit motor sequence learning.

Editor's evaluation: Task-evoked metabolic demands of the posteromedial default mode network are shaped by dorsal attention and frontoparietal control networks

By Fault or by Default

AimsCurrently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity.Materials and methodsTwenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions.ResultsThree optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain’s main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants’ subjective feelings after drinking.ConclusionThe current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage.

Altered Functional and Structural Connectivity in a Schizophrenia Patient With Complete Agenesis of the Corpus Callosum

Increased default-mode variability is related to reduced task-performance and is evident in adults with ADHD.

Focal ischemic brain lesions primarily affect circumscribed brain regions and fiber tracts resulting in acute neurological deficits. Secondary damage because of apoptosis, inflammation, diaschisis, and neurodegeneration, however, can also affect remote brain areas and may result in a more widespread perturbation of entire functional networks even in the nonischemic hemisphere. Such network-wide effects may play a role in the development of poststroke cognitive impairment and may impose limits on functional recovery. Assessing the total effect of all these mechanisms onto the damaged and recovering brain may be clinically useful for better outcome prediction and identification of therapeutic targets because some of those processes (diaschisis and inflammation) are in principle reversible and the strengthening of alternative pathways by targeted intervention may promote recovery. From a practical clinical point of view, imaging methods which can be performed on clinical MRI scanners and do not require active patient participation are ideal candidates to perform such assessments. This topical review thus focuses on diffusion tensor imaging (DTI) MRI and resting-state functional MRI (RS-fMRI) as the most promising methods to this regard (Table). We briefly introduce the physiological background of each method and review current evidence for assessing connectivity in the context of motor recovery. View this table: Table. Comparison of Resting-State fMRI and Diffusion Tensor Imaging ### Principles of DTI Diffusion-based MRI methods are techniques that are sensitive to signals originating from freely moving water molecules in the tissue. Unrestricted movement in all 3 spatial directions results in isotropic diffusion. In the healthy human brain, highly organized white matter pathways consisting of tightly packed axons present a barrier to isotropic diffusion. This diffusion anisotropy is characterized by the preferential diffusion of water molecules parallel to the long axis of the fiber bundles with restricted diffusion perpendicular to the long axis.1 During DTI acquisitions, pairs of balanced diffusion-sensitizing field gradients are applied …

Decision letter: Disruption in structural–functional network repertoire and time-resolved subcortical fronto-temporoparietal connectivity in disorders of consciousness

The use of functional connectivity magnetic resonance imaging (fcMRI) in research involving preterm infants is relatively new, and its feasibility in this population is not fully established. However, fcMRI images reveal functional neural connections that may be useful in establishing the mechanisms of neuroprotective interventions in preterm infants. The aim of this study was to determine the feasibility of using fcMRI to measure differences in functional neural connections in nursing intervention studies. A pilot study was conducted as part of a longitudinal, randomized controlled trial (RCT) testing the effect of a feeding intervention on neurodevelopmental and clinical outcomes of preterm infants randomly assigned to one of two groups: a patterned feeding experience (PFE) group and a usual feeding care (UFC) group. The fcMRIs were done at term-equivalent age. Visual, motor, and default mode networks were analyzed. Seven infants were studied (four were in the PFE group, and three were in the UFC group). Participants were selected sequentially from the parent RCT. Clear images were obtained from all participants. Differences were noted among PFE and UFC infants: Infants receiving PFE were hyperconnective in the default mode (caudate, anterior cingulate cortex, and precuneus) and motor networks (middle temporal and middle occipital areas) and hypoconnective in others areas of the default mode (hippocampal and lingual regions) and motor networks (precentral and superior frontal cortices) relative to UFC infants. No differences were noted in visual networks. The feasibility of using fcMRI at term-equivalent age in preterm infants who participated in an RCT on the effect of a nursing intervention was shown. Differences in connectivity among infants by group were detected. Further research is needed to show the benefit of fcMRI in studies of preterm infants given the costs of the procedure as well as the uncertain relationship of this early outcome measure to long-term neurodevelopment.

The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated

SummaryFunctional dissociations in the brain observed during non-rapid eye movement (NREM) sleep have been associated with reduced information integration and impaired consciousness that accompany increasing sleep depth. Here, we explored the dynamical properties of large-scale functional brain networks derived from transient brain activity using functional magnetic resonance imaging. Spatial brain maps generally display significant modifications in terms of their tendency to occur across wakefulness and NREM sleep. Unexpectedly, almost all networks predominated in activity during NREM stage 2 before an abrupt loss of activity is observed in NREM stage 3. Yet, functional connectivity and mutual dependencies between these networks progressively broke down with increasing sleep depth. Thus, the efficiency of information transfer during NREM stage 2 is low despite the high attempt to communicate. Critically, our approach provides relevant data for evaluating functional brain network integrity and our findings robustly support a significant advance in our neural models of human sleep and consciousness.