Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective

Specific factors and methodological decisions influencing brain responses to sexual stimuli in women

Most of the neuroimaging studies on sexual behavior have been conducted with male participants, leading to men-based models of sexual arousal. Here, possible factors and methodological decisions that might influence brain responses to sexual stimuli, specifically for the inclusion of women, will be reviewed. Based on this review, we suggest that future studies consider the following factors: menstrual phase, hormonal contraception use, history of sexual or psychiatric disorders or diseases, and medication use. Moreover, when researching sexual arousal, we suggest future studies assess sexual orientation and preferences, that women should select visual sexual stimuli, and a longer duration than commonly used. This review is thought to represent a useful guideline for future research in sexual arousal, which hopefully will lead to a higher inclusion of women and therefore more accurate neurobiological models of sexual arousal.

The mid-term effects of carotid endarterectomy on cognition and regional neural activity analyzed with the amplitude of low frequency fluctuations technique

Purpose

The study aims to evaluate the mid-term effects of carotid endarterectomy (CEA) on cognition and resting-state functional magnetic resonance imaging (rs-fMRI) using the Amplitude of Low Frequency Fluctuations (ALFF) technique.

Methods

In this observational study, patients eligible for CEA were prospectively included. On the same day, within 1 week of the CEA procedure performed and 12 months after the CEA procedure, all patients underwent (i) an MRI examination for rs-fMRI analysis and (ii) a cognitive evaluation using the Italian version of the Mini-Mental State Examination (MMSE) corrected for age and schooling. Pre-CEA and post-CEA MMSE scores were evaluated using paired sample t-tests, adopting a p-value < 0.05 as statistical threshold. The ALFF technique was used for analyzing the differences between pre-CEA and post-CEA rs-fMRI scans in terms of regional neural activation. This was accomplished by applying non-parametric statistics based on randomization/permutation for cluster-level inferences, adopting a cluster-mass p-value corrected for false discovery < 0.05 for cluster threshold, and a p-uncorrected < 0.01 for the voxel threshold.

Results

Twenty asymptomatic patients were enrolled. The mean MMSE score resulted improved following CEA procedure (p-value = 0.001). The ALFF analysis identified a single cluster of 6260 voxels of increased regional neural activity following CEA, and no cluster of reduced activity. The majority of voxels covered the right precentral gyrus, the right middle frontal gyrus, and the anterior division of the cingulate gyrus.

Conclusion

Mid-term cognitive improvements observed after CEA are associated to increased regional neural activity of several cerebral regions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-021-02815-7.

Degree Centrality of a Brain Network Is Altered by Stereotype Threat: Evidences From a Resting-State Functional Magnetic Resonance Imaging Study

Previous studies have found the effects of stereotype threat (ST) on cognitive processes, emotions, and motivations which could account for the underperformance in domain tasks. Efficient brain function does not require the function of different brain regions during specific tasks, but it does require the brain networks on which information is transported. Based on these, the effects of ST on the degree centrality under the resting state of brain regions related to these processes were investigated under math-related ST. The results showed that RSDC was decreased in the left hippocampus and left middle occipital gyrus (MOC), while RSDC was increased in the left precuneus, the right angular gyrus (AG), and the right superior parietal gyrus (SPG) under ST. Interestingly, we also found that the right-left anterior temporal lobe (ATL) and the right hippocampus were negatively correlated with manipulation check (MC) score in the ST group, while the right-left ATL and the right hippocampus were positively correlated with MC score in the control group. These results might reflect those individuals who attempted to inhibit the negative emotions induced by the negative stereotypes under ST conditions while increasing the self-relevant processes by retrieving episodic memory or autobiographical memory.

Increased Homotopic Connectivity in the Prefrontal Cortex Modulated by Olanzapine Predicts Therapeutic Efficacy in Patients with Schizophrenia

Background

Previous studies have revealed the abnormalities in homotopic connectivity in schizophrenia. However, the relationship of these deficits to antipsychotic treatment in schizophrenia remains unclear. This study explored the effects of antipsychotic therapy on brain homotopic connectivity and whether the homotopic connectivity of these regions might predict individual treatment response in schizophrenic patients.

Methods

A total of 21 schizophrenic patients and 20 healthy controls were scanned by the resting-state functional magnetic resonance imaging. The patients received olanzapine treatment and were scanned at two time points. Voxel-mirrored homotopic connectivity (VMHC) and pattern classification techniques were applied to analyze the imaging data.

Results

Schizophrenic patients presented significantly decreased VMHC in the temporal and inferior frontal gyri, medial prefrontal cortex (MPFC), and motor and low-level sensory processing regions (including the fusiform gyrus and cerebellum lobule VI) relative to healthy controls. The VMHC in the superior/middle MPFC was significantly increased in the patients after eight weeks of treatment. Support vector regression (SVR) analyses revealed that VMHC in the superior/middle MPFC at baseline can predict the symptomatic improvement of the positive and negative syndrome scale after eight weeks of treatment.

Conclusions

This study demonstrated that olanzapine treatment may normalize decreased homotopic connectivity in the superior/middle MPFC in schizophrenic patients. The VMHC in the superior/middle MPFC may predict individual response for antipsychotic therapy. The findings of this study conduce to the comprehension of the therapy effects of antipsychotic medications on homotopic connectivity in schizophrenia.

EGb in the Treatment for Patients with VCI: A Systematic Review and Meta-Analysis

Background

Ginkgo biloba extract (EGb) is widely used to treat impairments in memory, cognition, activities of daily living, inflammation, edema, stroke, Alzheimer's dementia, and aging.

Aim

We aimed to evaluate the safety and efficacy of EGb in treating vascular cognitive impairment (VCI).

Methods

The systematic review was performed using the latest guidelines. We searched for EGb-related trials up to March 1, 2021, in four Chinese databases, three English databases, and clinical trial registry platforms. Randomized controlled trials (RCTs) were included if the study enrolled participants with VCI. Two reviewers independently extracted the data and critically appraised the study quality. Heterogeneity was quantified with I ². Both sensitivity and subgroup analyses were used to identify the sources of heterogeneity. Publication bias was assessed with funnel plots. We used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to rate the evidence quality. Outcomes included assessments using the Activities of Daily Living (ADL), Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Hasegawa Dementia Scale (HDS), Barthel Index (BI), Functional Activity Questionnaire (FAQ), and adverse events.

Results

In this study, a total of 2019 patients in 23 RCTs were included. EGb appeared to be more effective than control conditions as assessed by the results of cognitive function evaluation, including MMSE (MD_{MMSE,EGb vs.blank} = 3.04, 95% CI: 0.10-5.98; MD_{MMSE,EGb vs.drugs for VCI} = 2.70, 95% CI: 1.39-4.01; MD_{MMSE,EGb+drugs for VCI vs.blank} = 5.90, 95% CI: 4.21-7.59; and MD_{MMSE,EGb+drugs for VCI vs.drugs for VCI} = 3.14, 95% CI: 2.14-4.15), MoCA (MD_{MoCA,EGb vs.blank} = 5.30, 95% CI: 2.15-8.46; MD_{MoCA,EGb+drugs for VCI vs.blank} = 2.66, 95% CI: 1.82-3.50; and MD_{MoCA,EGb+drugs for VCI vs.drugs for VCI} = 2.56, 95% CI: 1.85-3.27), HDS (MD_{HDS,EGb vs.blank} = 6.50; 95% CI: 4.86-8.14; MD_{HDS,EGb+drugs for VCI vs.drugs for VCI} = 3.60, 95% CI: 2.50-4.70), ADL (MD_{ADL,EGb vs.blank} = 7.20, 95% CI: 3.28-11.12; MD_{ADL,EGb+drugs for VCI vs.blank} = 10.00, 95% CI: 7.51-12.49; and MD_{ADL,EGb+drugs for VCI vs.drugs for VCI} = 9.20, 95% CI: 7.26-11.14), BI (MD_{BI,EGb+drugs for VCI vs.drugs for VCI} = 5.71, 95% CI: 2.99-8.43; MD_{FAQ,EGb vs.drugs for VCI} = -1.43, 95% CI: -2.78 to 0.08), and FAQ (MD_{FAQ,EGb+drugs for VCI vs.drugs for VCI} = -2.17, 95% CI: -4.13 to 0.21). Evidence of certainty ranged from medium certainty to very low certainty.

Conclusion

This meta-analysis showed that EGb may be an effective and safe treatment in improving MMSE, MOCA, ADL, and BI for VCI patients within three months of diagnosis. However, given the quality of the included RCTs, more preregistered trials are needed that explicitly examine the efficacy of EGb. This systematic review has been registered on PROSPERO, with the registration number CRD42021232967.

Seed-based test-retest reliability of resting state functional magnetic resonance imaging at 3T and 7T

PURPOSE

Ultrahigh field (UHF) resting state functional magnetic resonance imaging (rsfMRI) has become increasingly available for clinical and basic research, bringing improvements in resolution and contrast over standard high field imaging. Despite these improvements, UHF connectivity studies present several challenges, including increased sensitivity to physiological confounds and a vastly increased data burden. We present a direct quantitative assessment of test-retest reliability of functional connectivity in several standard functional networks between subjects scanned at 3T and 7T.

METHODS

Five healthy subjects were scanned over four sessions each in a scan-rescan design at both 3T and 7T field strengths. Resting state fMRI data were segmented into four major intrinsic connectivity networks, and seed-based peak correlations within and between these networks examined. The reliability of these correlations was assessed using intra-class correlation coefficients (ICC).

RESULTS

Across all data, over 4000 peak correlations were extracted for assessment. The reliability over all intrinsic networks was greater at 7T than 3T (median ICC 0.40 vs. 0.33, p ≤ 0.0014), with each network individually showing improvement. Inter-network reliability was stronger than intra-network reliability, but intra-network reliability showed the greatest improvement between field strengths.

CONCLUSION

We demonstrate significantly increased reliability of resting state connectivity at UHF strengths over conventional field strengths using a novel hybrid seed-based analysis. This result adds to the growing body of work supporting the migration of functional imaging studies to UHFs.

Altered trigeminothalamic spontaneous low-frequency oscillations in migraine without aura: a resting-state fMRI study

Background

Recent resting-state fMRI studies demonstrated functional dysconnectivity within the central pain matrix in migraineurs. This study aimed to investigate the spatial distribution and amplitude of low-frequency oscillations (LFOs) using fractional amplitude of low-frequency fluctuation (fALFF) analysis in migraine patients without aura, and to examine relationships between regional LFOs and clinical variables.

Methods

Resting-state fMRI data were obtained and preprocessed in 44 migraine patients without aura and 31 matched controls. fALFF was computed according to the original method, z-transformed for standardization, and compared between migraineurs and controls. Correlation analysis between regional fALFF and clinical variables was performed in migraineurs as well.

Results

Compared with controls, migraineurs had significant fALFF increases in bilateral ventral posteromedial (VPM) thalamus and brainstem encompassing rostral ventromedial medulla (RVM) and trigeminocervical complex (TCC). Regional fALFF values of bilateral VPM thalamus and brainstem positively correlated with disease duration, but not with migraine attack frequency or Migraine Disability Assessment Scale score.

Conclusions

We have provided evidence for abnormal LFOs in the brainstem including RVM/TCC and thalamic VPM nucleus in migraine without aura, implicating trigeminothalamic network oscillations in migraine pathophysiology. Our results suggest that enhanced LFO activity may underpin the interictal trigeminothalamic dysrhythmia that could contribute to the impairments of pain transmission and modulation in migraine. Given our finding of increasing fALFF in relation to increasing disease duration, the observed trigeminothalamic dysrhythmia may indicate either an inherent pathology leading to migraine headaches or a consequence of repeated attacks on the brain.

Alterations in brain structure and function in patients with osteonecrosis of the femoral head: a multimodal MRI study

Background

Pain, a major symptom of osteonecrosis of the femoral head (ONFH), is a complex sensory and emotional experience that presents therapeutic challenges. Pain can cause neuroplastic changes at the cortical level, leading to central sensitization and difficulties with curative treatments; however, whether changes in structural and functional plasticity occur in patients with ONFH remains unclear.

Methods

A total of 23 ONFH inpatients who did not undergo surgery (14 males, nine females; aged 55.61 ± 13.79 years) and 20 controls (12 males, eight females; aged 47.25 ± 19.35 years) were enrolled. Functional indices of the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and a structural index of tract-based spatial statistics (TBSS) were calculated for each participant. The probability distribution of fiber direction was determined according to the ALFF results.

Results

ONFH patients demonstrated increased ALFF in the bilateral dorsolateral superior frontal gyrus, right medial superior frontal gyrus, right middle frontal gyrus, and right supplementary motor area. In contrast, ONFH patients showed decreased ReHo in the left superior parietal gyrus and right inferior temporal gyrus. There were no significant differences in TBSS or probabilistic tractography.

Conclusion

These results indicate cerebral pain processing in ONFH patients. It is advantageous to use functional magnetic resonance imaging to better understand pain pathogenesis and identify new therapeutic targets in ONFH patients.

Long-term stability of the cortical volumetric profile and the functional human connectome throughout childhood and adolescence

There is compelling evidence showing that between-subject variability in several functional and structural brain features is sufficient for unique identification in adults. However, individuation of brain functional connectomes depends on the stabilization of neurodevelopmental processes during childhood and adolescence. Here, we aimed to (1) evaluate the intra-subject functional connectome stability over time for the whole brain and for large scale functional networks and (2) determine the long-term identification accuracy or 'fingerprinting' for the cortical volumetric profile and the functional connectome. For these purposes, we analysed a longitudinal cohort of 239 children and adolescents scanned in two sessions with an interval of approximately 3 years (age range 6-15 years at baseline and 9-18 years at follow-up). Corroborating previous results using short between-scan intervals in children and adolescents, we observed a moderate identification accuracy (38%) for the whole functional profile. In contrast, identification accuracy using cortical volumetric profile was 95%. Among the large-scale networks, the default-mode (26.8%), the frontoparietal (23.4%) and the dorsal-attention (27.6%) networks were the most discriminative. Our results provide further evidence for a protracted development of specific individual structural and functional connectivity profiles.

Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior

Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, that is, should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple noncontiguous components; therefore, we considered three areal-level MS-HBM variants spanning these range of possibilities. Individual-specific MS-HBM parcellations estimated using 10 min of data generalized better than other approaches using 150 min of data to out-of-sample rs-fMRI and task-fMRI from the same individuals. Resting-state functional connectivity derived from MS-HBM parcellations also achieved the best behavioral prediction performance. Among the three MS-HBM variants, the strictly contiguous MS-HBM exhibited the best resting-state homogeneity and most uniform within-parcel task activation. In terms of behavioral prediction, the gradient-infused MS-HBM was numerically the best, but differences among MS-HBM variants were not statistically significant. Overall, these results suggest that areal-level MS-HBMs can capture behaviorally meaningful individual-specific parcellation features beyond group-level parcellations. Multi-resolution trained models and parcellations are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Kong2022_ArealMSHBM).

Connectivity Patterns in the Core Resting-State Networks and Their Influence on Cognition

Introduction: Three prominent resting-state networks (rsNW) (default mode network [DMN], salience network [SN], and central executive network [CEN]) are recognized for their important role in several neuropsychiatric conditions. However, our understanding of their relevance in terms of cognition remains insufficient. Materials and Methods: In response, this study aims at investigating the patterns of different network properties (resting-state activity [RSA] and short- and long-range functional connectivity [FC]) in these three core rsNWs, as well as the dynamics of age-associated changes and their relation to cognitive performance in a sample of healthy controls (N = 74) covering a large age span (20-79 years). Using a whole-network based approach, three measures were calculated from the functional magnetic resonance imaging (fMRI) data: amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and degree of network centrality (DC). The cognitive test battery covered the following domains: memory, executive functioning, processing speed, attention, and visual perception. Results: For all three fMRI measures (ALFF, ReHo, and DC), the highest values of spontaneous brain activity (ALFF), short- and long-range connectivity (ReHo, DC) were observed in the DMN and the lowest in the SN. Significant age-associated decrease was observed in the DMN for ALFF and DC, and in the SN for ALFF and ReHo. Significant negative partial correlations were observed for working memory and ALFF in all three networks, as well as for additional cognitive parameters and ALFF in CEN. Discussion: Our results show that higher RSA in the three core rsNWs may have an unfavorable effect on cognition. Conversely, the pattern of network properties in healthy subjects included low RSA and FC in the SN. This complements previous research related to the three core rsNW and shows that the chosen approach can provide additional insight into their function.

Atypical Integration of Sensory-to-Transmodal Functional Systems Mediates Symptom Severity in Autism

A notable characteristic of autism spectrum disorder (ASD) is co-occurring deficits in low-level sensory processing and high-order social interaction. While there is evidence indicating detrimental cascading effects of sensory anomalies on the high-order cognitive functions in ASD, the exact pathological mechanism underlying their atypical functional interaction across the cortical hierarchy has not been systematically investigated. To address this gap, here we assessed the functional organisation of sensory and motor areas in ASD, and their relationship with subcortical and high-order trandmodal systems. In a resting-state fMRI data of 107 ASD and 113 neurotypical individuals, we applied advanced connectopic mapping to probe functional organization of primary sensory/motor areas, together with targeted seed-based intrinsic functional connectivity (iFC) analyses. In ASD, the connectopic mapping revealed topological anomalies (i.e., excessively more segregated iFC) in the motor and visual areas, the former of which patterns showed association with the symptom severity of restricted and repetitive behaviors. Moreover, the seed-based analysis found diverging patterns of ASD-related connectopathies: decreased iFCs within the sensory/motor areas but increased iFCs between sensory and subcortical structures. While decreased iFCs were also found within the higher-order functional systems, the overall proportion of this anomaly tends to increase along the level of cortical hierarchy, suggesting more dysconnectivity in the higher-order functional networks. Finally, we demonstrated that the association between low-level sensory/motor iFCs and clinical symptoms in ASD was mediated by the high-order transmodal systems, suggesting pathogenic functional interactions along the cortical hierarchy. Findings were largely replicated in the independent dataset. These results highlight that atypical integration of sensory-to-high-order systems contributes to the complex ASD symptomatology.

Altered regional homogeneity in patients with ovarian cancer treated with chemotherapy: a resting state fMRI study

Many patients treated with chemotherapy for non-central nervous system (CNS) cancers experience cognitive dysfunction. However, few studies have investigated treatment-related neurotoxicity in women with ovarian cancer. The goal of this study was to assess regional brain function in patients with ovarian cancer after first-line chemotherapy. Seventeen patients with ovarian cancer and seventeen healthy controls matched for gender, age and education participated in the study. The patients were evaluated 1-4 months after completion of first line taxane/platinum chemotherapy. All participants underwent resting state functional MRI (rsfMRI) and regional homogeneity (ReHo) indices were calculated. The results showed that patients had significantly decreased average ReHo values in the left middle frontal gyrus, medial prefrontal cortex, and right superior parietal lobule, compared to healthy controls. This is the first rsfMRI study showing ReHo alterations in frontal and parietal regions in patients with ovarian cancer treated with first-line chemotherapy. The findings are overall congruent with prior studies in non-CNS cancer populations and provide supporting evidence for the prevailing notion that frontal areas are particularly vulnerable to the adverse effects of chemotherapy.

Nodal Memberships to Communities of Functional Brain Networks Reveal Functional Flexibility and Individualized Connectome

Human brain network is organized as interconnected communities for supporting cognition and behavior. Despite studies on the nonoverlapping communities of brain network, overlapping community structure and its relationship to brain function remain largely unknown. With this consideration, we employed the Bayesian nonnegative matrix factorization to decompose the functional brain networks constructed from resting-state fMRI data into overlapping communities with interdigitated mapping to functional subnetworks. By examining the heterogeneous nodal membership to communities, we classified nodes into three classes: Most nodes in somatomotor and limbic subnetworks were affiliated with one dominant community and classified as unimodule nodes; most nodes in attention and frontoparietal subnetworks were affiliated with more than two communities and classified as multimodule nodes; and the remaining nodes affiliated with two communities were classified as bimodule nodes. This three-class paradigm was highly reproducible across sessions and subjects. Furthermore, the more likely a node was classified as multimodule node, the more flexible it will be engaged in multiple tasks. Finally, the FC feature vector associated with multimodule nodes could serve as connectome "fingerprinting" to gain high subject discriminability. Together, our findings offer new insights on the flexible spatial overlapping communities that related to task-based functional flexibility and individual connectome "fingerprinting."

What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

Learning Brain Functional Networks with Latent Temporal Dependency for MCI Identification

AbstractResting-state functional magnetic resonance imaging (rs-fMRI) has become a popular non-invasive way of diagnosing neurological disorders or their early stages by probing functional connectivity between different brain regions of interest (ROIs) across subjects. In the past decades, researchers have proposed many methods to estimate brain functional networks (BFNs) based on blood-oxygen-level-dependent (BOLD) signals captured by rs-fMRI. However, most of the existing methods estimate BFNs under the assumption that signals are independently sampled, which ignores the temporal dependency and sequential order of different time points (or volumes). To address this problem, in this paper, we first propose a novel BFN estimation model by introducing a latent variable to control the sequence of volumes for encoding the temporal dependency and sequential information of signals into the estimated BFNs. Then, we develop an efficient learning algorithm to solve the proposed model by the alternating optimization scheme. To verify the effectiveness of the proposed method, the estimated BFNs are used to identify subjects with mild cognitive impairment (MCIs) from normal controls (NCs). Experimental results show that our method outperforms the baseline methods in the sense of classification performance.

Hypostability in the default mode network and hyperstability in the frontoparietal control network of dynamic functional architecture during rumination

The neural underpinnings of rumination can be characterized by its specific dynamic nature. Temporal stability is the stable and consistent representation of information by a distributed neural activity and connectivity pattern across brain regions. Although stability is a key feature of the brain's functional architecture, its profiles supporting rumination remain elusive. We characterized the stability of the whole-brain functional architecture during an induced, continuous rumination state and compared it with a well-constrained distraction state as the control condition in a group of healthy participants (N = 40). We further examined the relationship between stability in regions showing a significant effect on the rumination vs. distraction contrast and rumination traits. The variability of dynamic functional connectivities (FCs) among these regions was also explored to determine the potential coupling regions that drove the altered stability pattern during rumination. The results showed that rumination was characterized by a similar but altered stability profile compared with distraction and resting states. Comparison between rumination and distraction revealed that key regions of the default mode network (DMN), such as the medial prefrontal cortex (MPFC) and bilateral parahippocampal gyrus (PHG), which showed decreased stability while frontoparietal control network (FPCN) regions, including the inferior parietal lobule (IPL) and dorsal lateral prefrontal cortex (DLPFC), showed significantly enhanced stability in rumination compared with distraction. Additionally, stability in the MPFC and IPL was related to individual differences in rumination traits. Exploratory analysis of the variation in dynamic FCs suggested that higher stability in the IPL may be related to its less variable FCs with the PHG. Together, these findings implicated that rumination may be supported by the dissociated dynamic nature of hypostability in the DMN and hyperstability in the FPCN.

Alterations of Regional Homogeneity in the Mild and Moderate Stages of Parkinson's Disease

Objectives: This study aimed to investigate alterations in regional homogeneity (ReHo) in early Parkinson's disease (PD) at different Hoehn and Yahr (HY) stages and to demonstrate the relationships between altered brain regions and clinical scale scores. Methods: We recruited 75 PD patients, including 43 with mild PD (PD-mild; HY stage: 1.0-1.5) and 32 with moderate PD (PD-moderate; HY stage: 2.0-2.5). We also recruited 37 age- and sex-matched healthy subjects as healthy controls (HC). All subjects underwent neuropsychological assessments and a 3.0 Tesla magnetic resonance scanning. Regional homogeneity of blood oxygen level-dependent (BOLD) signals was used to characterize regional cerebral function. Correlative relationships between mean ReHo values and clinical data were then explored. Results: Compared to the HC group, the PD-mild group exhibited increased ReHo values in the right cerebellum, while the PD-moderate group exhibited increased ReHo values in the bilateral cerebellum, and decreased ReHo values in the right superior temporal gyrus, the right Rolandic operculum, the right postcentral gyrus, and the right precentral gyrus. Reho value of right Pre/Postcentral was negatively correlated with HY stage. Compared to the PD-moderate group, the PD-mild group showed reduced ReHo values in the right superior orbital gyrus and the right rectus, in which the ReHo value was negatively correlated with cognition. Conclusion: The right superior orbital gyrus and right rectus may serve as a differential indicator for mild and moderate PD. Subjects with moderate PD had a greater scope for ReHo alterations in the cortex and compensation in the cerebellum than those with mild PD. PD at HY stages of 2.0-2.5 may already be classified as Braak stages 5 and 6 in terms of pathology. Our study revealed the different patterns of brain function in a resting state in PD at different HY stages and may help to elucidate the neural function and early diagnosis of patients with PD.

Abnormal degree centrality in lifelong premature ejaculation patients: an fMRI study

Lifelong premature ejaculation (PE) is one of the most prevalent male sexual dysfunctions. It is still not well known about the possible neural mechanisms of lifelong PE. This study tried to investigate the abnormal characteristics of brain functional networks of lifelong PE and to assess relationships of PE-related functional abnormalities with clinical symptoms. Functional magnetic resonance imaging (fMRI) data and clinical symptoms were collected from 45 lifelong PE patients and 37 healthy controls (HCs) since 2016, including disease and sexual life history, intravaginal ejaculatory latency time measured by stopwatch and other scales. The degree centrality (DC) approach were applied to distinguish altered brain functions between the two groups (p < 0.05, false discovery rate corrected). Correlation analysis was then performed to examine relationships between the imaging findings and clinical symptoms (p < 0.05, Bonferroni corrected). Results showed that compared with HCs, lifelong PE patients had increased DC value in the medial prefrontal cortex (mPFC), precuneus and primary somatosensory cortex (SI) as well as decreased DC value in the insula and orbitofrontal cortex. After controlling for anxiety and depression levels, the significant difference in the mPFC was not found. The DC value in the SI positively correlated with premature ejaculation diagnostic tool (PEDT) score in the patients. The present findings indicate that lifelong PE patients have altered DC in brain regions involved in sensation, motivation and inhibitory control processing. Our study may improve our understanding and provide a new sight into the further research of lifelong PE.

Common and specific neural correlates underlying insight and ordinary problem solving

Previous studies have investigated the cognitive and neural mechanisms underlying insight problem solving (INPS). However, it is still unclear which mechanisms are common to both INPS and ordinary problem solving (ORPS), and which are distinctly involved in only one of these processes. In this study, we selected two types of Chinese character chunk decompositions, ordinary Chinese character chunk decomposition (OCD) and creative Chinese character chunk decomposition (CCD), as representatives of ORPS and INPS, respectively. By using functional magnetic resonance imaging (fMRI) to record brain activations when subjects executed OCD or CCD operations, we found that both ORPS and INPS resulted in significant activations in the widespread frontoparietal cognitive control network, including the middle frontal gyrus, inferior frontal gyrus, and inferior parietal lobe. Furthermore, compared with ORPS, INPS led to greater activations in higher-level brain regions related to symbolic processing in the default mode network, including the anterior cingulate cortex, superior temporal gyrus, angular gyrus, and precuneus. Conversely, ORPS induced greater activations than INPS in more posterior brain regions related to visuospatial attention and visual perception, such as the inferior temporal gyrus, hippocampus, and middle occipital gyrus/superior parietal gyrus/fusiform gyrus. In addition, an ROI analysis corroborated the neural commonalities and differences between ORPS and INPS. These findings provide new evidence that ORPS and INPS rely on common as well as distinct cognitive processes and cortical mechanisms.

MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping

Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms (χ₁₃, χ₂₃ and χ₃₃) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ₃₃ and phase induced by χ₁₃ and χ₂₃ terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications.

Development of Frontal EEG Differences Between Eyes-Closed and Eyes-Open Resting Conditions in Children: Data From a Single-Channel Dry-Sensor Portable Device

Changes in EEG when moving from an eyes-closed to an eyes-open resting condition result from bottom-up sensory processing and have been referred to as activation. In children, activation is characterized by a global reduction in alpha, frontally present reductions for delta and theta, and a frontal increase for beta. The present study aimed to replicate frontal EEG activation effects using single-channel, dry-sensor EEG, and to extend current understanding by examining developmental change in children. Frontal EEG was recorded using a single-channel, dry-sensor EEG device while 182 children aged 7 to 12 years completed eyes-closed resting (EC), eyes-open resting (EO), and focus (FO) tasks. Results indicated that frontal delta, theta, and alpha power were reduced, and frontal beta power was increased, in the EO compared with the EC condition. Exploratory analysis of a form of top-down activation showed that frontal beta power was increased in the FO compared with to the EO condition, with no differences for other bands. The activation effects were robust at the individual level. The bottom-up activation effects reduced with age for frontal delta and theta, increased for frontal alpha, with no developmental change for top-down or bottom-up frontal beta activation. These findings contribute further to validation of the single-channel, dry-sensor, frontal EEG and provide support for use in a range of medical, therapeutic, and clinical domains.

Goal setting and attaining: Neural correlates of positive coping style and hope

Trait hope focuses on individual goal-related thoughts and is assumed to be a critical indicator for one's mental health. However, the neurobiological basis of hope and the neurological mechanisms underlying the relationship between positive coping style (PCS) and hope (including the two dimensions of pathway thinking and agency thinking) are still largely unknown. Thus, this study explored the neural basis of trait hope by correlating the regional amplitude of low-frequency fluctuations (ALFF) and resting-state functional connectivity (RSFC) with the self-reported hope of 576 healthy first-year college students underwent RS-fMRI. Our results showed that trait hope was positively associated with PCS. A whole-brain correlation analysis provided early evidence that higher levels of trait hope were associated with decreased ALFF in the left frontal pole cortex (FPC). Additionally, pathway thinking was associated with decreased ALFF in FPC, increased ALFF in the right postcentral gyrus (PCG), decreased RSFC of the left FPC and left posterior cingulate cortex, the left FPC and right middle temporal gyrus, and the right PCG and left cerebellum. Furthermore, mediation analyses demonstrated that the PCG-cerebellum connectivity might link to pathway thinking through PCS and PCS might relate to trait hope through PCG-cerebellum connectivity. Our findings contribute to the neurobiological basis of hope and the neural mechanism underlying the relationship between trait hope and coping style.

Longitudinal stability of resting-state networks in normal aging, mild cognitive impairment, and Alzheimer's disease

Test-retest reliability is essential for using resting-state functional magnetic resonance imaging (rs-fMRI) as a potential biomarker for Alzheimer's disease (AD), especially when monitoring longitudinal changes and treatment effects. In addition, test-retest variability itself might represent a feature of AD. Using 3.0 T rs-fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we examined the long-term (1-year) test-retest reliability of resting-state networks (RSNs) in 31 healthy elderly subjects, 63 patients with mild cognitive impairment (MCI), and 17 patients with AD by applying temporal concatenation group independent component analysis and dual regression. The intraclass correlation coefficient estimates of RSN amplitudes ranged from 0.44 to 0.77 in healthy elderly subjects, from 0.31 to 0.62 in patients with MCI, and from -0.06 to 0.44 in patients with AD. The overall test-retest reliability of RSNs was lower in patients with MCI than in healthy elderly subjects, and was lower in patients with AD than in patients with MCI. The differences in the test-retest reliabilities were due to the RSN amplitudes rather than the RSN shapes. Head motion was not significantly different among the three groups of subjects. The results indicate that the test-retest stability of RSNs generally declines with progression to MCI and AD, mainly due to the RSN amplitudes rather than the RSN shapes. The test-retest instability in MCI and AD may reflect progressive neurofunctional alterations related to the pathology of AD.

Regional Spontaneous Neural Activity Alterations in Type 2 Diabetes Mellitus: A Meta-Analysis of Resting-State Functional MRI Studies

Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed inconsistent regional spontaneous neural activity alterations in patients with type 2 diabetes mellitus (T2DM). The aim of our meta-analysis was to identify concordant regional spontaneous neural activity abnormalities in patients with T2DM. Methods: A systematic search was conducted to identify voxel-based rs-fMRI studies comparing T2DM patients with healthy controls. The permutation of subject images seed-based d mapping (SDM) was used to quantitatively estimate the regional spontaneous neural activity abnormalities in patients with T2DM. Metaregression was conducted to examine the associations between clinical characteristics and functional alterations. Results: A total of 16 studies with 19 datasets including 434 patients with T2DM and 391 healthy controls were included. Patients with T2DM showed hypoactivity in the right medial superior frontal gyrus, right superior temporal gyrus, and left lingual gyrus, whereas hyperactivity in the right cerebellum. Metaregression analysis identified negative correlation between regional activity in the medial superior frontal and anterior cingulate gyri and illness duration of patients with T2DM. Conclusion: The patterns of regional spontaneous neural activity alterations, characterized by hypoactivity in the medial pre-frontal cortex, visual cortex, and superior temporal gyrus, whereas hyperactivity in the cerebellum, might represent the underlying neuropathological mechanisms of T2DM.

The coupling of BOLD signal variability and degree centrality underlies cognitive functions and psychiatric diseases

Brain signal variability has been consistently linked to functional integration; however, whether this coupling is associated with cognitive functions and/or psychiatric diseases has not been clarified. Using multiple multimodality datasets, including resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP: N = 927) and a Beijing sample (N = 416) and cerebral blood flow (CBF) and rsfMRI data from a Hangzhou sample (N = 29), we found that, compared with the existing variability measure (i.e., SD_BOLD), the mean-scaled (standardized) fractional standard deviation of the BOLD signal (mfSD_BOLD) maintained very high test-retest reliability, showed greater cross-site reliability and was less affected by head motion. We also found strong reproducible couplings between the mfSD_BOLD and functional integration measured by the degree centrality (DC), both cross-voxel and cross-subject, which were robust to scanning and preprocessing parameters. Moreover, both mfSD_BOLD and DC were correlated with CBF, suggesting a common physiological basis for both measures. Critically, the degree of coupling between mfSD_BOLD and long-range DC was positively correlated with individuals' cognitive total composite scores. Brain regions with greater mismatches between mfSD_BOLD and long-range DC were more vulnerable to brain diseases. Our results suggest that BOLD signal variability could serve as a meaningful index of local function that underlies functional integration in the human brain and that a strong coupling between BOLD signal variability and functional integration may serve as a hallmark of balanced brain networks that are associated with optimal brain functions.

Implications from translational cross-validation of clinical assessment tools for diagnosis and treatment in psychiatry

Traditional therapeutic methods in psychiatry, such as psychopharmacology and psychotherapy help many people suffering from mental disorders, but in the long-term prove to be effective in a relatively small proportion of those affected. Therapeutically, resistant forms of mental disorders such as schizophrenia, major depressive disorder, and bipolar disorder lead to persistent distress and dysfunction in personal, social, and professional aspects. In an effort to address these problems, the translational approach in neuroscience has initiated the inclusion of novel or modified unconventional diagnostic and therapeutic techniques with promising results. For instance, neuroimaging data sets from multiple modalities provide insight into the nature of pathophysiological mechanisms such as disruptions of connectivity, integration, and segregation of neural networks, focusing on the treatment of mental disorders through instrumental biomedical methods such as electro-convulsive therapy (ECT), transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS). These methodologies have yielded promising results that have yet to be understood and improved to enhance the prognosis of the severe and persistent psychotic and affective disorders. The current review is focused on the translational approach in the management of schizophrenia and mood disorders, as well as the adaptation of new transdisciplinary diagnostic tools such as neuroimaging with concurrently administered psychopathological questionnaires and integration of the results into the therapeutic framework using various advanced instrumental biomedical tools such as ECT, TMS, tDCS and DBS.

The Relationship Between Behavioral Inhibition and Approach Motivation Systems (BIS/BAS) and Intrinsic Brain Network Connectivity in Adult Cannabis Users

Dampened behavioral inhibition and overactive behavioral approach motivation systems (i.e. BIS/BAS) are associated with cannabis use disorder (CUD), although the underlying neural mechanisms of these alterations have not yet been examined. The brain’s executive control network (ECN) plays a role in decision-making and is associated with BIS/BAS. In this study, we tested the hypothesis that altered ECN resting-state functional connectivity (rsFC) underlies dysfunctional behavioral inhibition and approach motivation in cannabis users. To that end, we collected resting-state functional magnetic resonance imaging scans in 86 cannabis using adults and 59 non-using adults to examine group differences in the relationship between ECN rsFC and BIS/BAS. Our results showed that BIS was positively correlated with left ECN rsFC in cannabis users, while it was positively correlated with right ECN rsFC in non-users. There was a trend-level moderation effect of group on the association between BIS/BAS and ECN rsFC, showing a weaker association in BIS/BAS and ECN rsFC in cannabis users compared to non-users. An exploratory mediation analysis found that the severity of CUD mediated the relationship between users’ BIS scores and left ECN rsFC. These findings suggest that cannabis use may lead to dysregulation in typical ECN functional organization related to BIS/BAS.

"Impact of ICA Dimensionality on the Test-Retest Reliability of Resting-State Functional Connectivity

As resting-state functional connectivity (rsFC) research moves toward the study of individual differences, test-retest reliability is increasingly important to understand. Previous literature supports the test-retest reliability of rsFC derived with independent component analysis (ICA) and dual regression, yet the impact of dimensionality (i.e., the number of components to extract from group-ICA) remained obscure in the current context of large-scale datasets. To provide principled guidelines on this issue, ICA at dimensionalities varying from 25 to 350 was applied to the cortical surface with resting-state functional magnetic resonance imaging data from 1003 participants in the Human Connectome Project. The reliability of two rsFC measures: (within-component) coherence and (between-component) connectivity was estimated. Reliability and its change with dimensionality varied by network: the cognitive (frontoparietal, cingulo-opercular, dorsal attention, and default) networks were measured with the highest reliability which improved with increased dimensionality until at least 150; the visual and somatomotor networks were measured with lower reliability which benefited mildly from increased dimensionality; the temporal pole/orbitofrontal cortex (TP/OFC) network was measured with the lowest reliability. Overall, ICA reliability was optimized at dimensionalities of 150 or above. Compared with two popular binary, non-overlapping cortical atlases, ICA and dual regression resulted in higher reliability for the cognitive networks, lower reliability for the somatomotor network, and similar reliability for the visual and TP/OFC networks. These findings highlight analytical decisions that maximize the reliability of rsFC measures and how they depend on one's networks of interest.

Aberrant brain functional hubs and causal connectivity in presbycusis

To investigate resting-state connectivity and further understand directional aspects of implicit alterations in presbycusis patients, we used degree centrality (DC) and Granger causality analysis (GCA) to detect functional hubs of the whole-brain network and then analyze directional connectivity. Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 40 presbycusis patients and 40 healthy controls matched for age, gender, and education. We used DC analysis and GCA to characterize abnormal brain networks in presbycusis patients. The associations of network centrality and directed functional connectivity (FC) with clinical measures of presbycusis were also examined according to the above results. We found that the network centrality of left frontal middle gyrus (MFG) was significantly lower than that of healthy control group. Unidirectionally, the left MFG revealed increased directional connectivity to the left superior frontal gyrus (SFG), while the left MFG exhibited decreased directional connectivity to the left middle temporal gyrus (MTG) and right lingual gyrus (LinG). And the decreased directional connectivity was found from the left precentral gyrus (PrCG) to the left MFG. In addition, the Trail-Making Test B (TMT-B) score was negatively correlated with the decreased DC of the left MFG (r = -0.359, p = 0.032). Resting-state fMRI provides a novel method for identifying aberrant brain network architecture. These results primarily indicate altered functional hubs and abnormal frontal lobe connectivity patterns that may further reflect executive dysfunction in patients with presbycusis.

Cell-Type-Specific Gene Modules Related to the Regional Homogeneity of Spontaneous Brain Activity and Their Associations With Common Brain Disorders

Mapping gene expression profiles to neuroimaging phenotypes in the same anatomical space provides opportunities to discover molecular substrates for human brain functional properties. Here, we aimed to identify cell-type-specific gene modules associated with the regional homogeneity (ReHo) of spontaneous brain activity and their associations with brain disorders. Fourteen gene modules were consistently associated with ReHo in the three datasets, five of which showed cell-type-specific expression (one neuron-endothelial module, one neuron module, one astrocyte module and two microglial modules) in two independent cell series of the human cerebral cortex. The neuron-endothelial module was mainly enriched for transporter complexes, the neuron module for the synaptic membrane, the astrocyte module for amino acid metabolism, and microglial modules for leukocyte activation and ribose phosphate biosynthesis. In enrichment analyses of cell-type-specific modules for 10 common brain disorders, only the microglial module was significantly enriched for genes obtained from genome-wide association studies of multiple sclerosis (MS) and Alzheimer's disease (AD). The ReHo of spontaneous brain activity is associated with the gene expression profiles of neurons, astrocytes, microglia and endothelial cells. The microglia-related genes associated with MS and AD may provide possible molecular substrates for ReHo abnormality in both brain disorders.

Intranasal vasopressin modulates resting state brain activity across multiple neural systems: Evidence from a brain imaging machine learning study

Arginine vasopressin (AVP), a neuropeptide with widespread receptors in brain regions important for socioemotional processing, is critical in regulating various mammalian social behavior and emotion. Although a growing body of task-based brain imaging studies have revealed the effects of AVP on brain activity associated with emotion processing, social cognition and behaviors, the potential modulations of AVP on resting-state brain activity remain largely unknown. Here, the current study addressed this issue by adopting a machine learning approach to distinguish administration of AVP and placebo, employing the amplitude of low-frequency fluctuation (ALFF) as a measure of resting-state brain activity. The brain regions contributing to the classification were then subjected to functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that ALFF across multiple neural systems were sufficient to distinguish between AVP and placebo at individual level, with the contributing regions distributed across the social cognition network, sensorimotor regions and emotional processing network. These findings suggest that the role of AVP in socioemotional functioning recruits multiple brain networks distributed across the whole brain rather than specific localized neural pathways. Beyond these findings, the current data-driven approach also opens a novel avenue to delineate neural underpinnings of various neuropeptides or hormones.

Changes in Degree Centrality of Network Nodes in Different Frequency Bands in Parkinson's Disease With Depression and Without Depression

Background

Depression induces an early onset of Parkinson’s disease (PD), aggravates dyskinesia and cognitive impairment, and accelerates disease progression. However, it is very difficult to identify and diagnose PD with depression (PDD) in the early clinical stage. Few studies have suggested that the changes in neural networks are associated with PDD, while degree centrality (DC) has been documented to be effective in detecting brain network changes.

Objectives

The objectives of this study are to explore DC changes between patients with PDD and without depression (PDND) and to find the key brain hubs involved with depression in PD patients.

Methods

One hundred and four PD patients and 54 healthy controls (HCs) underwent brain resting-state functional magnetic resonance imaging. The Data Processing and Analysis of Brain Imaging and Resting-State Functional Magnetic Resonance Data Analysis Toolkit were used for processing and statistical analysis. The DC value of each frequency band was calculated. One-way analysis of variance and a two-sample t-test for post hoc comparison were used to compare the differences of the DC values in different frequency bands among PDD, PDND, and healthy control group. Gaussian random field was used for multiple comparison correction. Pearson correlation analysis was performed between each individual’s DC map and clinical indicators.

Results

The DC value of different brain regions changed in PDD and PDND in different frequency bands. The prefrontal lobe, limbic system, and basal ganglia were the main brain regions involved. PDD patients showed a wider range and more abnormal brain areas in the slow-4 frequency band (0.027–0.073 Hz) compared to the HCs. PDD showed a decreased DC value in the medial frontal gyrus, bilateral cuneus gyrus, right lingual gyrus, bilateral supplementary motor area (SMA), bilateral superior frontal gyrus, and left paracentral lobule, but an increased DC value in the bilateral brainstem, midbrain, bilateral parahippocampal gyrus, cerebellum, left superior temporal gyrus, bilateral insula, left fusiform gyrus, and left caudate nucleus in the traditional frequency band (0.01–0.08 Hz) compared to PDND patients. PDND patients displayed more abnormal functions in the basal ganglia in the slow-4 frequency band.

Conclusion

The DC changes in PDD and PDND are frequency dependent and frequency specific. The medial frontal gyrus, SMA, and limbic system may be the key hubs for depression in PD.

Nicotine addiction: Translational insights from circuit neuroscience

Contemporary neuroscience aims to understand how neuronal activity produces internal processes and observable behavioral states. This aim crucially depends on systems-level, circuit-based analyses of the working brain, as behavioral states arise from information flow and connectivity within and between discrete and overlapping brain regions, forming circuits and networks. Functional magnetic resonance imaging (fMRI), offers a key to advance circuit neuroscience; fMRI measures inter and intra- regional circuits at behaviorally relevant spatial-temporal resolution. Herein, we argue that cross-sectional observations in human populations can be best understood via mechanistic and causal insights derived from brain circuitry obtained from preclinical fMRI models. Using nicotine addiction as an exemplar of a circuit-based substance use disorder, we review fMRI-based observations of a circuit that was first shown to be disrupted among human smokers and was recently replicated in rodent models of nicotine dependence. Next, we discuss circuits that predispose to nicotine dependence severity and their interaction with circuits that change as a result of chronic nicotine administration using a rodent model of dependence. Data from both clinical and preclinical fMRI experiments argue for the utility of fMRI studies in translation and reverse translation of a circuit-based understanding of brain disease states. We conclude by discussing the future of circuit neuroscience and functional neuroimaging as an essential bridge between animal models and human populations to the understanding of brain function in health and disease.

Towards robust and replicable sex differences in the intrinsic brain function of autism

BACKGROUND

Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data.

METHODS

We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research.

RESULTS

Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples-EU-AIMS LEAP.

LIMITATIONS

Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability.

CONCLUSIONS

Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.

Coordination between frontolimbic resting state connectivity and hypothalamic-pituitary-adrenal axis functioning in adolescents with and without depression

Depression is associated with abnormalities in Hypothalamic-Pituitary-Adrenal (HPA) axis functioning and neural circuitry that underlie the stress response. Resting-state functional connectivity (RSFC) between frontolimbic brain regions captures intrinsic connections that may set the stage for the rallying and regulating of the HPA axis system. This study examined the association between cortisol stress response and frontolimbic (amygdala and ventral and dorsal medial prefrontal cortex [vmPFC and dmPFC respectively]) RSFC in 88 (Age: M = 15.95, SD = 2.04; 71.60% female) adolescents with (N = 55) and without (N = 33) major depressive disorder (MDD). We collected salivary cortisol in the context of a modified Trier Social Stress Test (TSST) paradigm. Key findings were that adolescents with depression and healthy controls showed different patterns of association between amygdala and vmPFC RSFC and HPA functioning: while healthy controls showed a positive relationship between frontolimbic connectivity and cortisol levels that may indicate coordination across neural and neuroendocrine systems, adolescents with depression showed a minimal or inverse relationship, suggesting poor coordination of these systems. Results were similar when examining non-suicidal self-injury subgroups within the MDD sample. These findings suggest that the intrinsic quality of this frontolimbic connection may be related to HPA axis functioning. In MDD, inverse associations may represent a compensatory response in one system in response to dysfunction in the other. Longitudinal multilevel research, however, is needed to disentangle how stress system coordination develops in normal and pathological contexts and how these systems recover with treatment.

Morphometric and Functional Brain Connectivity Differentiates Chess Masters From Amateur Players

A common task in brain image analysis includes diagnosis of a certain medical condition wherein groups of healthy controls and diseased subjects are analyzed and compared. On the other hand, for two groups of healthy participants with different proficiency in a certain skill, a distinctive analysis of the brain function remains a challenging problem. In this study, we develop new computational tools to explore the functional and anatomical differences that could exist between the brain of healthy individuals identified on the basis of different levels of task experience/proficiency. Toward this end, we look at a dataset of amateur and professional chess players, where we utilize resting-state functional magnetic resonance images to generate functional connectivity (FC) information. In addition, we utilize T1-weighted magnetic resonance imaging to estimate morphometric connectivity (MC) information. We combine functional and anatomical features into a new connectivity matrix, which we term as the functional morphometric similarity connectome (FMSC). Since, both the FC and MC information is susceptible to redundancy, the size of this information is reduced using statistical feature selection. We employ off-the-shelf machine learning classifier, support vector machine, for both single- and multi-modality classifications. From our experiments, we establish that the saliency and ventral attention network of the brain is functionally and anatomically different between two groups of healthy subjects (chess players). We argue that, since chess involves many aspects of higher order cognition such as systematic thinking and spatial reasoning and the identified network is task-positive to cognition tasks requiring a response, our results are valid and supporting the feasibility of the proposed computational pipeline. Moreover, we quantitatively validate an existing neuroscience hypothesis that learning a certain skill could cause a change in the brain (functional connectivity and anatomy) and this can be tested via our novel FMSC algorithm.

Voxel-Mirrored Homotopic Connectivity Associated With Change of Cognitive Function in Chronic Pontine Stroke

Recent neuroimaging studies have shown the possibility of cognitive impairment after pontine stroke. In this study, we aimed to use voxel-mirrored homotopic connectivity (VMHC) to investigate changes in the cognitive function in chronic pontine stroke. Functional MRI (fMRI) and behavioral assessments of cognitive function were obtained from 56 patients with chronic pontine ischemic stroke [28 patients with left-sided pontine stroke (LP) and 28 patients with right-sided pontine stroke (RP)] and 35 matched healthy controls (HC). The one-way ANOVA test was performed for the three groups after the VMHC analysis. Results showed that there were significant decreases in the bilateral lingual gyrus (Lingual_L and Lingual_R) and the left precuneus (Precuneus_L) in patients with chronic pontine ischemic stroke compared to HCs. However, in a post-hoc multiple comparison test, this difference remained only between the HC and RP groups. Moreover, we explored the relationship between the decreased z-values in VMHC and the behavior-task scores using a Pearson's correlation test and found that both scores of short-term memory and long-term memory in the Rey Auditory Verbal Learning Test were positively correlated with z-values of the left lingual gyrus (Lingual_L), the right lingual gyrus (Lingual_R), and the left precuneus (Precuneus_L) in VMHC. Besides that, the z-values of Precuneus_L in VMHC were also negatively correlated with the reaction time for correct responses in the Flanker task and the spatial memory task. In conclusion, first, the lingual gyrus played an important role in verbal memory. Second, the precuneus influenced the working memory, both auditory-verbal memory and visual memory. Third, the right-sided stroke played a greater role in the results of this study. This study provides a basis for further elucidation of the characteristics and mechanisms of cognitive impairment after pontine stroke.

Observing Plasticity of the Auditory System: Volumetric Decreases Along with Increased Functional Connectivity in Aspiring Professional Musicians

Playing music relies on several sensory systems and the motor system, and poses strong demands on control processes, hence, offering an excellent model to study how experience can mold brain structure and function. Although most studies on neural correlates of music expertise rely on cross-sectional comparisons, here we compared within-person changes over time in aspiring professionals intensely preparing for an entrance exam at a University of the Arts to skilled amateur musicians not preparing for a music exam. In the group of aspiring professionals, we observed gray-matter volume decrements in left planum polare, posterior insula, and left inferior frontal orbital gyrus over a period of about 6 months that were absent among the amateur musicians. At the same time, the left planum polare, the largest cluster of structural change, showed increasing functional connectivity with left and right auditory cortex, left precentral gyrus, left supplementary motor cortex, left and right postcentral gyrus, and left cingulate cortex, all regions previously identified to relate to music expertise. In line with the expansion-renormalization pattern of brain plasticity (Wenger et al., 2017a. Expansion and renormalization of human brain structure during skill acquisition. Trends Cogn Sci. 21:930-939.), the aspiring professionals might have been in the selection and refinement period of plastic change.

Functional network alterations differently associated with suicidal ideas and acts in depressed patients: an indirect support to the transition model

The transition from suicidal ideas to a suicide act is an important topic of research for the identification of those patients at risk of acting out. We investigated here whether specific brain activity and connectivity measures at rest may be differently associated with suicidal thoughts and behaviors. A large sample of acutely depressed patients with major depressive disorder was recruited in three different centers (Montreal/Canada, Stanford/USA, and Jena/Germany), covering four different phenotypes: patients with a past history of suicide attempt (n = 53), patients with current suicidal ideas but no past history of suicide attempt (n = 40), patients without current suicidal ideation nor past suicide attempts (n = 42), and healthy comparison subjects (n = 107). 3-T resting-state functional magnetic resonance imaging (fMRI) measures of the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were obtained and examined in a whole-brain data-driven analysis. Past suicide attempt was associated with a double cortico-subcortical dissociation in ALFF values. Decreased ALFF and DC values mainly in a frontoparietal network and increased ALFF values in some subcortical regions (hippocampus and thalamus) distinguished suicide attempters from suicide ideators, patient controls, and healthy controls. No clear neural differences were identified in relation to suicidal ideas. Suicide attempters appear to be a distinct subgroup of patients with widespread brain alterations in functional activity and connectivity that could represent factors of vulnerability. Our results also indirectly support at the neurobiological level the relevance of the transition model described at the psychological and clinical levels. The brain bases of suicidal ideas occurrence in depressed individuals needs further investigations.

Impact of concatenating fMRI data on reliability for functional connectomics

Compelling evidence suggests the need for more data per individual to reliably map the functional organization of the human connectome. As the notion that 'more data is better' emerges as a golden rule for functional connectomics, researchers find themselves grappling with the challenges of how to obtain the desired amounts of data per participant in a practical manner, particularly for retrospective data aggregation. Increasingly, the aggregation of data across all fMRI scans available for an individual is being viewed as a solution, regardless of scan condition (e.g., rest, task, movie). A number of open questions exist regarding the aggregation process and the impact of different decisions on the reliability of resultant aggregate data. We leveraged the availability of highly sampled test-retest datasets to systematically examine the impact of data aggregation strategies on the reliability of cortical functional connectomics. Specifically, we compared functional connectivity estimates derived after concatenating from: 1) multiple scans under the same state, 2) multiple scans under different states (i.e. hybrid or general functional connectivity), and 3) subsets of one long scan. We also varied connectivity processing (i.e. global signal regression, ICA-FIX, and task regression) and estimation procedures. When the total number of time points is equal, and the scan state held constant, concatenating multiple shorter scans had a clear advantage over a single long scan. However, this was not necessarily true when concatenating across different fMRI states (i.e. task conditions), where the reliability from the aggregate data varied across states. Concatenating fewer numbers of states that are more reliable tends to yield higher reliability. Our findings provide an overview of multiple dependencies of data concatenation that should be considered to optimize reliability in analysis of functional connectivity data.

Structural and functional alterations in untreated patients with major depressive disorder and bipolar disorder experiencing first depressive episode: A magnetic resonance imaging study combined with follow-up

BACKGROUND

Magnetic resonance imaging (MRI) could assist in identifying objective biomarkers and follow-up study could effectively improve subjective diagnostic accuracy. By combining MRI with follow-up, this study aims to determine the shared and distinct alterations between major depressive disorder (MDD) and bipolar disorder (BD).

METHODS

Untreated patients with MDD experiencing the first episode were subjected to MRI and subsequent follow-up. Fifteen patients with mania or hypomania were regrouped into BD group. Twenty patients were still grouped as MDD after an average of 37.95 months follow-up. Thirty healthy controls (HCs) were recruited to match the patients. Gray matter volume (GMV) and amygdala-seed functional connectivity (FC) in the whole brain were detected and compared among the three groups.

RESULTS

GMV analysis revealed that the MDD and BD groups presented reduced GMV predominantly in the parietal, occipital, and frontal regions in the bilateral cerebrum compared with the HCs. The BD group had reduced GMV predominantly in the parietal, temporal, insular regions and the Rolandic operculum in the right-side cerebrum compared with MDD and HC groups. FC analysis revealed that the MDD and BD patients displayed increased FC values mainly in the bilateral parietal, and left occipital regions. Only the BD group displayed increased FC values in the temporal, occipital, parietal and limbic regions in the right-side cerebrum relative to HCs.

LIMITATIONS

The main limitation is the relatively small sample size.

CONCLUSIONS

Alterations in the cortical regions and cortico-limbic neural system may provide the scientific basis for differential diagnosis in affective disorders.

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test-retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed - a process likely to be limited for most due to the lack of test-retest samples to enable parameter optimization.

Anxiety in Parkinson's disease: Abnormal resting activity and connectivity

Anxiety is a very common yet poorly understood symptom of Parkinson's disease. We investigated whether Parkinson's disease patients experiencing anxiety share neural mechanisms described in the general population with involvement of critical regions for the control of behaviour and movement. Thirty-nine patients with PD were recruited for this study, 20 with higher anxiety scores and 19 with lower anxiety scores. They all underwent a resting-state fMRI scan, while they were on medication. The amplitude of low-frequency fluctuation (ALFF) and seed-based connectivity were investigated to reveal the changes of the spontaneous activity and the interaction among different related regions. The results provided evidence that anxiety in Parkinson's disease is associated with the over-activation of the amygdala and impaired inter-relationship of regions involved in behavior (i.e. medial prefrontal cortex, insula) and motor control (i.e. basal ganglia).

Abnormal intrinsic functional hubs and connectivity in stable patients with COPD: a resting-state MRI study

Chronic obstructive pulmonary disease (COPD) affects a large population and is closely associated with cognitive impairment. However, the mechanisms of cognitive impairment in COPD patients have not been unraveled. This study investigated the change in patterns of intrinsic functional hubs using a degree centrality (DC) analysis. The connectivity between these abnormal hubs with the remaining brain was also investigated using functional connectivity (FC). Nineteen stable patients with COPD and 20 normal controls(NC) underwent functional magnetic resonance imaging (MRI) examinations and clinical and neuropsychologic assessments. We measured the voxel-wise DC across the whole brain gray matter and the seed-based FC between these abnormal hubs in the remaining brain matter; the group difference was calculated. A partial correlation analysis was performed to assess the relationship between the abnormal DC and clinical variables in COPD patients. Compared to NC, the patients with COPD exhibited significantly decreased DC in the right lingual gyrus (LG), bilateral supplementary motor area (SMA), and right paracentral lobule (PCL). A further seed-based FC analysis found that COPD patients demonstrated significantly decreased FC between these abnormal hubs in several brain areas, including the left cerebellum anterior lobe, left lingual gyrus, left fusiform gyrus, right insula, right inferior frontal gyrus, limbic lobe, cingulate gyrus, left putamen, lentiform nucleus, right precuneus, and right paracentral lobule. A partial correlation analysis showed that the decreased DC in the right PCL was positively correlated with the FEV1 and FEV1/FVC, and the decreased DC in the SMA was positively correlated with naming and pH in COPD patients. This study demonstrates that there are intrinsic functional hubs and connectivity alterations that may reflect the aberrant information communication in the brain of COPD patients. These findings may help provide new insight for understanding the mechanisms of COPD-related cognitive impairment from whole brain functional connections.

Neurovascular coupling alterations in type 2 diabetes: a 5-year longitudinal MRI study

INTRODUCTION

Respective alterations in resting-state brain neural activity and cerebral blood flow (CBF) in type 2 diabetes mellitus (T2DM) have been reported. However, their coupling alteration in T2DM remains largely unknown.

RESEARCH DESIGN AND METHODS

Twenty-seven patients with T2DM aged 40-67 years and 36 well-matched healthy controls (HCs) underwent resting-state functional MRI (rs-fMRI) and arterial spin labeling (ASL) scans at two time points with a 5-year interval. Regional homogeneity (ReHo) and CBF were calculated from rs-fMRI and ASL, respectively. The standardized ReHo:CBF ratio (mReHo:mCBF ratio), the spontaneous neuronal activity per unit CBF supply, was compared between the two time points. Relationships between the mReHo:mCBF ratio and memory performance were analyzed.

RESULTS

Over 5 years, decreased mReHo:mCBF ratios in patients with T2DM were mainly distributed in four regions, among which the left insula exhibited more severely decreased mReHo:mCBF ratio in patients with T2DM than in HCs, while the left postcentral gyrus, the right Rolandic operculum, and the right precentral gyrus showed no significant intergroup difference. Correlations between the mReHo:mCBF ratio and memory performance were also found in patients with T2DM.

CONCLUSIONS

This study suggests that T2DM may accelerate neurovascular coupling impairment in specific brain regions (the left insula), contributing to memory decline. This study implies that the mReHo:mCBF ratio is a potential imaging marker for detecting neurovascular changes.

Abnormal Degree Centrality in White Matter Hyperintensities: A Resting-State Functional Magnetic Resonance Imaging Study

Background: White matter hyperintensities (WMHs) are a common occurrence with aging and are associated with cognitive impairment. However, the neurobiological mechanisms of WMHs remain poorly understood. Functional magnetic resonance imaging (fMRI) is a prominent tool that helps in non-invasive examinations and is increasingly used to diagnose neuropsychiatric diseases. Degree centrality (DC) is a common and reliable index in fMRI, which counts the number of direct connections for a given voxel in a network and reflects the functional connectivity within brain networks. We explored the underlying mechanism of cognitive impairment in WMHs from the perspective of DC. Methods: A total of 104 patients with WMHs and 37 matched healthy controls (HCs) were enrolled in the current study. All participants underwent individual and overall cognitive function tests and resting-state fMRI (rs-fMRI). WMHs were divided into three groups (39 mild WMHs, 37 moderate WMHs, and 28 severe WMHs) according to their Fazekas scores, and the abnormal DC values in the WMHs and HCs groups were analyzed. Results: There was a significant difference in the right inferior frontal orbital gyrus and left superior parietal gyrus between the WMHs and HCs groups. The functional connectivity between the right inferior frontal orbital gyrus and left inferior temporal gyrus, left superior parietal gyrus, and left parietal inferior gyrus was also different in the WMHs group. Conclusion: The change in DC value may be one of the underlying mechanisms of cognitive impairment in individuals with WMHs, which provides us with a new approach to delaying cognitive impairment in WMHs.