Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes

Temporal regularity of intrinsic cerebral activity in patients with chronic primary insomnia: a brain entropy study using resting-state fMRI

INTRODUCTION

Several neuroimaging studies have suggested that patients with chronic primary insomnia (CPI) exhibit anatomical and functional alterations of the brain, but the temporal regularity in spontaneous neuronal activity remains unknown. Here, brain entropy (BEN), a data-driven method used to measure the signal regularity of a time series, was applied for the first time to investigate changes in the entire brain at the voxel level.

METHODS

Resting-state functional MRI data were used to investigate insomnia-related BEN alterations and the resting-state functional connectivity (rsFC) pattern in seed regions with altered BEN in 29 patients with identified and untreated CPI and 29 matched healthy controls. Subsequently, within the CPI group, correlation analysis was conducted to evaluate the relationship between the clinical variables and the BEN and rsFC of the abnormal regions.

RESULTS

Chronic primary insomnia patients showed significant increase in BEN in the central part of the default-mode network (DMN), the anterior regions of the task-positive network (TPN), the hippocampus (Hipp), and basal ganglia (BG), and decreases in BEN in the right postcentral gyrus (PoCG) and right temporal-occipital junction (TOJ). We also demonstrated that three altered resting-state functional connectivity (rsFC) patterns were associated with abnormal BEN regions in CPI patients. Correlation analysis identified an association between the altered rsFC and clinical variables, such as the Pittsburgh Sleep Quality Index (PSQI), in CPI patients.

CONCLUSIONS

Together, these findings suggest that abnormal BEN-related intrinsic functional plasticity in CPI patients corresponds to poor sleep quality during chronic insomnia. Alterations in both BEN and its affected connectivity may improve our understanding of treatment-naïve CPI patients and promote the future development of new therapeutic strategies.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR.

Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps

Resting-state functional connectivity analysis has become a widely used method for the investigation of human brain connectivity and pathology. The measurement of neuronal activity by functional MRI, however, is impeded by various nuisance signals that reduce the stability of functional connectivity. Several methods exist to address this predicament, but little consensus has yet been reached on the most appropriate approach. Given the crucial importance of reliability for the development of clinical applications, we here investigated the effect of various confound removal approaches on the test-retest reliability of functional-connectivity estimates in two previously defined functional brain networks. Our results showed that gray matter masking improved the reliability of connectivity estimates, whereas denoising based on principal components analysis reduced it. We additionally observed that refraining from using any correction for global signals provided the best test-retest reliability, but failed to reproduce anti-correlations between what have been previously described as antagonistic networks. This suggests that improved reliability can come at the expense of potentially poorer biological validity. Consistent with this, we observed that reliability was proportional to the retained variance, which presumably included structured noise, such as reliable nuisance signals (for instance, noise induced by cardiac processes). We conclude that compromises are necessary between maximizing test-retest reliability and removing variance that may be attributable to non-neuronal sources.

Altered Vision-Related Resting-State Activity in Pituitary Adenoma Patients with Visual Damage

Objective

To investigate changes of vision-related resting-state activity in pituitary adenoma (PA) patients with visual damage through comparison to healthy controls (HCs).

Methods

25 PA patients with visual damage and 25 age- and sex-matched corrected-to-normal-vision HCs underwent a complete neuro-ophthalmologic evaluation, including automated perimetry, fundus examinations, and a magnetic resonance imaging (MRI) protocol, including structural and resting-state fMRI (RS-fMRI) sequences. The regional homogeneity (ReHo) of the vision-related cortex and the functional connectivity (FC) of 6 seeds within the visual cortex (the primary visual cortex (V1), the secondary visual cortex (V2), and the middle temporal visual cortex (MT+)) were evaluated. Two-sample t-tests were conducted to identify the differences between the two groups.

Results

Compared with the HCs, the PA group exhibited reduced ReHo in the bilateral V1, V2, V3, fusiform, MT+, BA37, thalamus, postcentral gyrus and left precentral gyrus and increased ReHo in the precuneus, prefrontal cortex, posterior cingulate cortex (PCC), anterior cingulate cortex (ACC), insula, supramarginal gyrus (SMG), and putamen. Compared with the HCs, V1, V2, and MT+ in the PAs exhibited decreased FC with the V1, V2, MT+, fusiform, BA37, and increased FC primarily in the bilateral temporal lobe (especially BA20,21,22), prefrontal cortex, PCC, insular, angular gyrus, ACC, pre-SMA, SMG, hippocampal formation, caudate and putamen. It is worth mentioning that compared with HCs, V1 in PAs exhibited decreased or similar FC with the thalamus, whereas V2 and MT+ exhibited increased FCs with the thalamus, especially pulvinar.

Conclusions

In our study, we identified significant neural reorganization in the vision-related cortex of PA patients with visual damage compared with HCs. Most subareas within the visual cortex exhibited remarkable neural dysfunction. Some subareas, including the MT+ and V2, exhibited enhanced FC with the thalamic pulvinar, which indicates an important role in the compensatory mechanism following visual impairment. In addition, neural dysfunction within the visual cortex was associated with neural activity alternation in the higher-order cognitive cortex, especially subareas in default mode network (DMN) and salience network (SN).

Reduced spontaneous neuronal activity in the insular cortex and thalamus in healthy adults with insomnia symptoms

Poor sleep and insomnia have been recognized to be strongly correlated with the development of depression. The exploration of the basic mechanism of sleep disturbance could provide the basis for improved understanding and treatment of insomnia and prevention of depression. In this study, 31 subjects with insomnia symptoms as measured by the Hamilton Rating Scale for Depression (HAMD-17) and 71 age- and gender-matched subjects without insomnia symptoms were recruited to participate in a clinical trial. Using resting-state functional magnetic resonance imaging (rs-fMRI), we examined the alterations in spontaneous brain activity between the two groups. Correlations between the fractional amplitude of low frequency fluctuations (fALFF) and clinical measurements (e.g., insomnia severity and Hamilton Depression Rating Scale [HAMD] scores) were also tested in all subjects. Compared to healthy participants without insomnia symptoms, participants with insomnia symptoms showed a decreased fALFF in the left ventral anterior insula, bilateral posterior insula, left thalamus, and pons but an increased fALFF in the bilateral middle occipital gyrus and right precentral gyrus. More specifically, a significant, negative correlation of fALFF in the left thalamus with early morning awakening scores and HAMD scores in the overall sample was identified. These results suggest that insomnia symptoms are associated with altered spontaneous activity in the brain regions of several important functional networks, including the insular cortex of the salience and the thalamus of the hyperarousal network. The altered fALFF in the left thalamus supports the "hyperarousal theory" of insomnia symptoms, which could serve as a biomarker for insomnia.

The Neuro Bureau ADHD-200 Preprocessed repository

In 2011, the "ADHD-200 Global Competition" was held with the aim of identifying biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic resonance imaging (rs-fMRI) and structural MRI (s-MRI) data collected on 973 individuals. Statisticians and computer scientists were potentially the most qualified for the machine learning aspect of the competition, but generally lacked the specialized skills to implement the necessary steps of data preparation for rs-fMRI. Realizing this barrier to entry, the Neuro Bureau prospectively collaborated with all competitors by preprocessing the data and sharing these results at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) (http://www.nitrc.org/frs/?group_id=383). This "ADHD-200 Preprocessed" release included multiple analytical pipelines to cater to different philosophies of data analysis. The processed derivatives included denoised and registered 4D fMRI volumes, regional time series extracted from brain parcellations, maps of 10 intrinsic connectivity networks, fractional amplitude of low frequency fluctuation, and regional homogeneity, along with grey matter density maps. The data was used by several teams who competed in the ADHD-200 Global Competition, including the winning entry by a group of biostaticians. To the best of our knowledge, the ADHD-200 Preprocessed release was the first large public resource of preprocessed resting-state fMRI and structural MRI data, and remains to this day the only resource featuring a battery of alternative processing paths.

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network).

METHODS

We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction.

RESULTS

Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD.

CONCLUSIONS

Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD.

Disrupted Brain Functional Network Architecture in Chronic Tinnitus Patients

Purpose: Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated the disruptions of multiple brain networks in tinnitus patients. Nonetheless, several studies found no differences in network processing between tinnitus patients and healthy controls (HCs). Its neural bases are poorly understood. To identify aberrant brain network architecture involved in chronic tinnitus, we compared the resting-state fMRI (rs-fMRI) patterns of tinnitus patients and HCs.

Materials and Methods: Chronic tinnitus patients (n = 24) with normal hearing thresholds and age-, sex-, education- and hearing threshold-matched HCs (n = 22) participated in the current study and underwent the rs-fMRI scanning. We used degree centrality (DC) to investigate functional connectivity (FC) strength of the whole-brain network and Granger causality to analyze effective connectivity in order to explore directional aspects involved in tinnitus.

Results: Compared to HCs, we found significantly increased network centrality in bilateral superior frontal gyrus (SFG). Unidirectionally, the left SFG revealed increased effective connectivity to the left middle orbitofrontal cortex (OFC), left posterior lobe of cerebellum (PLC), left postcentral gyrus, and right middle occipital gyrus (MOG) while the right SFG exhibited enhanced effective connectivity to the right supplementary motor area (SMA). In addition, the effective connectivity from the bilateral SFG to the OFC and SMA showed positive correlations with tinnitus distress.

Conclusions: Rs-fMRI provides a new and novel method for identifying aberrant brain network architecture. Chronic tinnitus patients have disrupted FC strength and causal connectivity mostly in non-auditory regions, especially the prefrontal cortex (PFC). The current findings will provide a new perspective for understanding the neuropathophysiological mechanisms in chronic tinnitus.

Functional Connectivity of the Infant Human Brain: Plastic and Modifiable

Infancy is a critical and immensely important period in human brain development. Subtle changes during this stage may be greatly amplified with the unfolding of different developmental processes, exerting far-reaching consequences. Studies of the structure and behavioral manifestations of the infant brain are fruitful. However, the specific functional brain mechanisms that enable the execution of different behaviors remained elusive until the advent of functional connectivity fMRI (fcMRI), which provides an unprecedented opportunity to probe the infant functional brain development in vivo. Since its inception, a burgeoning field of infant brain functional connectivity study has emerged and thrived during the past decade. In this review, we describe (1) findings of normal development of functional connectivity networks and their relationships to behaviors and (2) disruptions of the normative functional connectivity development due to identifiable genetic and/or environmental risk factors during the first 2 years of human life. Technical considerations of infant fcMRI are also provided. It is our hope to consolidate previous findings so that the field can move forward with a clearer picture toward the ultimate goal of fcMRI-based objective methods for early diagnosis/identification of risks and evaluation of early interventions to optimize developing functional connectivity networks in this critical developmental window.

Thalamocortical functional connectivity and behavioral disruptions in neonates with prenatal cocaine exposure

Prenatal cocaine exposure (PCE) affects neurobehavioral development, however, disentangling direct drug-related mechanisms from contextual effects (e.g., socioeconomic status) has proven challenging in humans. The effects of environmental confounds are minimal immediately after birth thus we aimed to delineate neurobehavioral correlates of PCE in a large cohort of neonates (2-6weeks of age, N=152) with and without drug exposure using resting state functional magnetic resonance imaging (rsfMRI) and developmental assessments at 3months with the Bayley Scales of Infant & Toddler Development, 3rd edition. The cohort included healthy controls and neonates with similar poly-drug exposure±cocaine. We focused on the thalamus given its critical importance in early brain development and its unique positioning in the dopamine system. Our results revealed PCE-related hyper-connectivity between the thalamus and frontal regions and a drug-common hypo-connective signature between the thalamus and motor-related regions. PCE-specific neonatal thalamo-frontal connectivity was inversely related to cognitive and fine motor scores and thalamo-motor connectivity showed a positive relationship with composite (gross plus fine) motor scores. Finally, cocaine by selective-serotonin-reuptake-inhibitor (SSRI) interactions were detected, suggesting the combined use of these drugs during pregnancy could have additional consequences on fetal development. Overall, our findings provide the first delineation of PCE-related disruptions of thalamocortical functional connectivity, neurobehavioral correlations, and drug-drug interactions during infancy.

Influences of Head Motion Regression on High-Frequency Oscillation Amplitudes of Resting-State fMRI Signals

High-frequency oscillations (HFOs, >0.1 Hz) of resting-state fMRI (rs-fMRI) signals have received much attention in recent years. Denoising is critical for HFO studies. Previous work indicated that head motion (HM) has remarkable influences on a variety of rs-fMRI metrics, but its influences on rs-fMRI HFOs are still unknown. In this study, we investigated the impacts of HM regression (HMR) on HFO results using a fast sampling rs-fMRI dataset. We demonstrated that apparent high-frequency (∼0.2–0.4 Hz) components existed in the HM trajectories in almost all subjects. In addition, we found that individual-level HMR could robustly reveal more between-condition (eye-open vs. eye-closed) amplitude differences in high-frequency bands. Although regression of mean framewise displacement (FD) at the group level had little impact on the results, mean FD could significantly account for inter-subject variance of HFOs even after individual-level HMR. Our findings suggest that HM artifacts should not be ignored in HFO studies, and HMR is necessary for detecting HFO between-condition differences.

Decoupling of large-scale brain networks supports the consolidation of durable episodic memories

At a large scale, the human brain is organized into modules of interconnected regions, some of which play opposing roles in supporting cognition. In particular, the Default-Mode Network (DMN) has been linked to operations on internal representations, while task-positive networks are recruited during interactions with the external world. Here, we test the hypothesis that the generation of durable long-term memories depends on optimal recruitment of such antagonistic large-scale networks. As long-term memory consolidation is a process ongoing for days and weeks after an experience, we propose that individuals characterized by strong decoupling of the DMN and task-positive networks at rest operate in a mode beneficial for the long-term stabilization of episodic memories. To capture network connectivity unaffected by transient task demands and representative of brain behavior outside an experimental setting, 87 participants were scanned during rest before performing an associative encoding task. To link individual resting-state functional connectivity patterns to time-dependent memory consolidation processes, participants were given an unannounced memory test, either after a brief interval or after a retention period of ~6 weeks. We found that participants with a resting state characterized by high synchronicity in a DMN-centered network system and low synchronicity between task-positive networks showed superior recollection weeks after encoding. These relationships were not observed for information probed only hours after encoding. Furthermore, the two network systems were found to be anticorrelated. Our results suggest that this memory-relevant antagonism between DMN and task-positive networks is maintained through complex regulatory interactions between the systems.

Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level

Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

Intrinsic Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Science in Development

Functional magnetic resonance imaging (fMRI) without an explicit task, i.e., resting state fMRI, of individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) is growing rapidly. Early studies were unaware of the vulnerability of this method to even minor degrees of head motion, a major concern in the field. Recent efforts are implementing various strategies to address this source of artifact along with a growing set of analytical tools. Availability of the ADHD-200 Consortium dataset, a large-scale multi-site repository, is facilitating increasingly sophisticated approaches. In parallel, investigators are beginning to explicitly test the replicability of published findings. In this narrative review, we sketch out broad, overarching hypotheses being entertained while noting methodological uncertainties. Current hypotheses implicate the interplay of default, cognitive control (frontoparietal) and attention (dorsal, ventral, salience) networks in ADHD; functional connectivities of reward-related and amygdala-related circuits are also supported as substrates for dimensional aspects of ADHD. Before these can be further specified and definitively tested, we assert the field must take on the challenge of mapping the "topography" of the analytical space, i.e., determining the sensitivities of results to variations in acquisition, analysis, demographic and phenotypic parameters. Doing so with openly available datasets will provide the needed foundation for delineating typical and atypical developmental trajectories of brain structure and function in neurodevelopmental disorders including ADHD when applied to large-scale multi-site prospective longitudinal studies such as the forthcoming Adolescent Brain Cognitive Development study.

Reliability and reproducibility of individual differences in functional connectivity acquired during task and resting state

OBJECTIVES

Application of fMRI connectivity metrics as diagnostic biomarkers at the individual level will require reliability, sensitivity and specificity to longitudinal changes in development, aging, neurocognitive, and behavioral performance and pathologies. Such metrics have not been well characterized for recent advances in BOLD acquisition.

EXPERIMENTAL DESIGN

Analysis of multiband BOLD data from the HCP 500 Subjects Release was performed with FIX ICA and with WM, CSF and motion parameter regression. Analysis with ROIs covering the gray matter at 5 mm resolution was performed to assess functional connectivity. ROIs in key areas were used to demonstrate statistical differences between specific connections. Reproducibility of group-mean functional connectivity and for single connections for individuals was evaluated for both resting state and task acquisitions.

PRINCIPAL OBSERVATIONS

Systematic differences in group-mean connectivity were demonstrated during task and rest and during different tasks, although individual differences in connectivity were maintained. Reproducibility of a single connection for a subject and across subjects for resting and task acquisition was demonstrated to be a linear function of the square root of imaging time. Randomly removing up to 50% of time points had little effect on reliability, while truncating an acquisition was associated with decreased reliability. Reliability was highest within the cortex, and lowest for deep gray nuclei, gray-white junction, and near large sulci.

CONCLUSIONS

This study found systematic differences in group-mean connectivity acquired during task and rest acquitisions and preserved individual differences in connectivity due to intrinsic differences in an individual's brain activity and structural brain architecture. We also show that longer scan times are needed to acquire data on single subjects for information on connections between specific ROIs. Longer scans may be facilitated by acquisition during task paradigms, which will systematically affect functional connectivity but may preserve individual differences in connectivity on top of task modulations.

Altered Intrinsic Regional Activity and Interregional Functional Connectivity in Post-stroke Aphasia

Several neuroimaging studies have examined cerebral function in patients who suffer from aphasia, but the mechanism underlying this disorder remains poorly understood. In this study, we examined alterations in the local regional and remote interregional network cerebral functions in aphasia combined with amplitude of low-frequency fluctuations and interregional functional connectivity (FC) using resting-state functional magnetic resonance imaging. A total of 17 post-stroke aphasic patients, all having suffered a stroke in the left hemisphere, as well as 20 age- and sex-matched healthy controls, were enrolled in this study. The aphasic patients showed significantly increased intrinsic regional activity mainly in the contralesional mesial temporal (hippocampus/parahippocampus, [HIP/ParaHIP]) and lateral temporal cortices. In addition, intrinsic regional activity in the contralesional HIP/ParaHIP was negatively correlated with construction score. Aphasic patients showed increased remote interregional FC between the contralesional HIP/ParaHIP and fusiform gyrus, but reduced FC in the ipsilesional occipital and parietal cortices. These findings suggested that the intrinsic regional brain dysfunctions in aphasia were related to interregional functional connectivity. Changes in the intrinsic regional brain activity and associated remote functional connectivity pattern would provide valuable information to enhance the understanding of the pathophysiological mechanisms of aphasia.

Tracking brain arousal fluctuations with fMRI

Changes in brain activity accompanying shifts in vigilance and arousal can interfere with the study of other intrinsic and task-evoked characteristics of brain function. However, the difficulty of tracking and modeling the arousal state during functional MRI (fMRI) typically precludes the assessment of arousal-dependent influences on fMRI signals. Here we combine fMRI, electrophysiology, and the monitoring of eyelid behavior to demonstrate an approach for tracking continuous variations in arousal level from fMRI data. We first characterize the spatial distribution of fMRI signal fluctuations that track a measure of behavioral arousal; taking this pattern as a template, and using the local field potential as a simultaneous and independent measure of cortical activity, we observe that the time-varying expression level of this template in fMRI data provides a close approximation of electrophysiological arousal. We discuss the potential benefit of these findings for increasing the sensitivity of fMRI as a cognitive and clinical biomarker.

Changes in the Vision-related Resting-state Network in Pituitary Adenoma Patients After Vision Improvement

Background:

The aim of this research was to investigate the changes in the vision-related resting-state network (V-RSN) in pituitary adenoma (PA) patients after vision improvement, which was induced by operative treatment.

Methods:

Ten PA patients with an improved visual acuity or/and visual field after transsphenoidal pituitary tumor resection were recruited and underwent a complete neuro-ophthalmologic evaluation, as well as an magnetic resonance imaging (MRI) protocol, including structural and resting-state functional MRI sequences before and after the operation. The regional homogeneity (ReHo) of the V-RSN was evaluated. Two sample t-test was performed to identify the significant differences in the V-RSN in the PA patients before and after transsphenoidal pituitary tumor resection.

Results:

Compared with the preoperation counterparts, the PA patients with improved vision after the operation exhibited reduced ReHo in the bilateral thalamus, globus pallidus, caudate nucleus, putamen nucleus, supplementary motor area, and left hippocampal formation, and increased ReHo in the bilateral cuneus gyrus, calcarine gyrus, right lingual gyrus, and fusiform gyrus.

Conclusions:

PA patients with improved vision exhibit increased neural activity within the visual cortex, but decreased neural activity in subareas of the multisensory and multimodal systems beyond the vision cortex.

Disrupted Intrinsic Local Synchronization in Poststroke Aphasia

Evidence has accumulated from the task-related and task-free (i.e., resting state) studies that alternations of intrinsic neural networks exist in poststroke aphasia (PSA) patients. However, information is lacking on the changes in the local synchronization of spontaneous functional magnetic resonance imaging blood-oxygen level-dependent fluctuations in PSA at rest. We investigated the altered intrinsic local synchronization using regional homogeneity (ReHo) on PSA (n = 17) and age- and sex-matched healthy controls (HCs) (n = 20). We examined the correlations between the abnormal ReHo values and the aphasia severity and language performance in PSA. Compared with HCs, the PSA patients exhibited decreased intrinsic local synchronization in the right lingual gyrus, the left calcarine, the left cuneus, the left superior frontal gyrus (SFG), and the left medial of SFG. The local synchronization (ReHo value) in the left medial of SFG was positively correlated with aphasia severity (r = 0.55, P = 0.027) and the naming scores of Aphasia Battery of Chinese (r = 0.66, P = 0.005). This result is consistent with the important role of this value in language processing even in the resting state. The pathogenesis of PSA may be attributed to abnormal intrinsic local synchronous in multiple brain regions.

Imaging the "At-Risk" Brain: Future Directions

OBJECTIVES

Clinical neuroscience is increasingly turning to imaging the human brain for answers to a range of questions and challenges. To date, the majority of studies have focused on the neural basis of current psychiatric symptoms, which can facilitate the identification of neurobiological markers for diagnosis. However, the increasing availability and feasibility of using imaging modalities, such as diffusion imaging and resting-state fMRI, enable longitudinal mapping of brain development. This shift in the field is opening the possibility of identifying predictive markers of risk or prognosis, and also represents a critical missing element for efforts to promote personalized or individualized medicine in psychiatry (i.e., stratified psychiatry).

METHODS

The present work provides a selective review of potentially high-yield populations for longitudinal examination with MRI, based upon our understanding of risk from epidemiologic studies and initial MRI findings.

RESULTS

Our discussion is organized into three topic areas: (1) practical considerations for establishing temporal precedence in psychiatric research; (2) readiness of the field for conducting longitudinal MRI, particularly for neurodevelopmental questions; and (3) illustrations of high-yield populations and time windows for examination that can be used to rapidly generate meaningful and useful data. Particular emphasis is placed on the implementation of time-appropriate, developmentally informed longitudinal designs, capable of facilitating the identification of biomarkers predictive of risk and prognosis.

CONCLUSIONS

Strategic longitudinal examination of the brain at-risk has the potential to bring the concepts of early intervention and prevention to psychiatry.

Amplitude of Low-Frequency Fluctuations in Multiple-Frequency Bands in Acute Mild Traumatic Brain Injury

Functional disconnectivity during the resting state has been observed in mild traumatic brain injury (mTBI) patients during the acute stage. However, it remains largely unknown whether the abnormalities are related to specific frequency bands of the low-frequency oscillations (LFO). Here, we used the amplitude of low-frequency fluctuations (ALFF) to examine the amplitudes of LFO in different frequency bands (slow-5: 0.01–0.027 Hz; slow-4: 0.027–0.073 Hz; and typical: 0.01–0.08 Hz) in patients with acute mTBI. A total of 24 acute mTBI patients and 24 age-, sex-, and education-matched healthy controls participated in this study. In the typical band, acute mTBI patients showed lower standardized ALFF in the right middle frontal gyrus and higher standardized ALFF in the right lingual/fusiform gyrus and left middle occipital gyrus. Further analyses showed that the difference between groups was concentrated in a narrower (slow-4) frequency band. In the slow-5 band, mTBI patients only exhibited higher standardized ALFF in the occipital areas. No significant correlation between the mini-mental state examination score and the standardized ALFF value was found in any brain region in the three frequency bands. Finally, no significant interaction between frequency bands and groups was found in any brain region. We concluded that the abnormality of spontaneous brain activity in acute mTBI patients existed in the frontal lobe as well as in distributed brain regions associated with integrative, sensory, and emotional roles, and the abnormal spontaneous neuronal activity in different brain regions could be better detected by the slow-4 band. These findings might contribute to a better understanding of local neural psychopathology of acute mTBI. Future studies should take the frequency bands into account when measuring intrinsic brain activity of mTBI patients.

Longitudinal Changes in Resting-State Cerebral Activity in Patients with First-Episode Schizophrenia: A 1-Year Follow-up Functional MR Imaging Study

Purpose To determine whether the brain functional abnormalities of drug-naive first-episode schizophrenia are reduced after 1 year of undergoing antipsychotic treatment and whether pretreatment resting-state functional magnetic resonance (MR) imaging parameters are associated with longitudinal changes in clinical symptoms. Materials and Methods This prospective study was approved by the local ethical committee, and written informed consent was obtained from all participants. Twenty antipsychotic-naive first-episode patients with schizophrenia and 16 healthy individuals were recruited and underwent resting-state functional MR imaging at baseline and again at 1-year follow-up, by which time significant clinical improvement was seen. The amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were analyzed with analysis of covariance. Results The amount of ALFF in the right inferior parietal lobule (IPL) and orbitofrontal cortex (OFC) and the amount of FC between the bilateral IPLs significantly increased over the follow-up period, and the amount of ALFF in the right occipital gyrus was reduced (P < .050, AlphaSim corrected [ http://afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf ]), returning toward normal levels. Furthermore, the degree of alteration in ALFF values in the right OFC (P = .037) and occipital gyrus (P = .002) at baseline was significantly correlated with the magnitude of the normalization in those regions at 1-year follow-up. In contrast, abnormalities of ALFF in the bilateral thalamus, ventral medial prefrontal cortex, precuneus, and right amygdala and of FC between the right OFC and the dorsal medial prefrontal cortex at baseline did not improve in patients at 1-year follow-up. Conclusion These findings show that some, but not all, neurophysiologic alterations that occur during the acute phase of schizophrenia are normalized in the context of clinical improvement and suggest therapeutic implications for exploration of which alterations in regional and network-level brain function evolve over time in patients with schizophrenia and which reflect persistent pathologic traits. Online supplemental material is available for this article.

Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis

Brain entropy (BEN) mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI), reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS), a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS) patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS) and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS.

Default mode network maturation and psychopathology in children and adolescents

BACKGROUND

The human default mode (DMN) is involved in a wide array of mental disorders. Current knowledge suggests that mental health disorders may reflect deviant trajectories of brain maturation.

METHOD

We studied 654 children using functional magnetic resonance imaging (fMRI) scans under a resting-state protocol. A machine-learning method was used to obtain age predictions of children based on the average coefficient of fractional amplitude of low frequency fluctuations (fALFFs) of the DMN, a measure of spontaneous local activity. The chronological ages of the children and fALFF measures from regions of this network, the response and predictor variables were considered respectively in a Gaussian Process Regression. Subsequently, we computed a network maturation status index for each subject (actual age minus predicted). We then evaluated the association between this maturation index and psychopathology scores on the Child Behavior Checklist (CBCL).

RESULTS

Our hypothesis was that the maturation status of the DMN would be negatively associated with psychopathology. Consistent with previous studies, fALFF significantly predicted the age of participants (p < .001). Furthermore, as expected, we found an association between the DMN maturation status (precocious vs. delayed) and general psychopathology scores (p = .011).

CONCLUSIONS

Our findings suggest that child psychopathology seems to be associated with delayed maturation of the DMN. This delay in the neurodevelopmental trajectory may offer interesting insights into the pathophysiology of mental health disorders.

Individual Variability and Test-Retest Reliability Revealed by Ten Repeated Resting-State Brain Scans over One Month

Individual differences in mind and behavior are believed to reflect the functional variability of the human brain. Due to the lack of a large-scale longitudinal dataset, the full landscape of variability within and between individual functional connectomes is largely unknown. We collected 300 resting-state functional magnetic resonance imaging (rfMRI) datasets from 30 healthy participants who were scanned every three days for one month. With these data, both intra- and inter-individual variability of six common rfMRI metrics, as well as their test-retest reliability, were estimated across multiple spatial scales. Global metrics were more dynamic than local regional metrics. Cognitive components involving working memory, inhibition, attention, language and related neural networks exhibited high intra-individual variability. In contrast, inter-individual variability demonstrated a more complex picture across the multiple scales of metrics. Limbic, default, frontoparietal and visual networks and their related cognitive components were more differentiable than somatomotor and attention networks across the participants. Analyzing both intra- and inter-individual variability revealed a set of high-resolution maps on test-retest reliability of the multi-scale connectomic metrics. These findings represent the first collection of individual differences in multi-scale and multi-metric characterization of the human functional connectomes in-vivo, serving as normal references for the field to guide the use of common functional metrics in rfMRI-based applications.

Lifespan anxiety is reflected in human amygdala cortical connectivity

The amygdala plays a pivotal role in processing anxiety and connects to large‐scale brain networks. However, intrinsic functional connectivity (iFC) between amygdala and these networks has rarely been examined in relation to anxiety, especially across the lifespan. We employed resting‐state functional MRI data from 280 healthy adults (18–83.5 yrs) to elucidate the relationship between anxiety and amygdala iFC with common cortical networks including the visual network, somatomotor network, dorsal attention network, ventral attention network, limbic network, frontoparietal network, and default network. Global and network‐specific iFC were separately computed as mean iFC of amygdala with the entire cerebral cortex and each cortical network. We detected negative correlation between global positive amygdala iFC and trait anxiety. Network‐specific associations between amygdala iFC and anxiety were also detectable. Specifically, the higher iFC strength between the left amygdala and the limbic network predicted lower state anxiety. For the trait anxiety, left amygdala anxiety–connectivity correlation was observed in both somatomotor and dorsal attention networks, whereas the right amygdala anxiety–connectivity correlation was primarily distributed in the frontoparietal and ventral attention networks. Ventral attention network exhibited significant anxiety–gender interactions on its iFC with amygdala. Together with findings from additional vertex‐wise analysis, these data clearly indicated that both low‐level sensory networks and high‐level associative networks could contribute to detectable predictions of anxiety behaviors by their iFC profiles with the amygdala. This set of systems neuroscience findings could lead to novel functional network models on neural correlates of human anxiety and provide targets for novel treatment strategies on anxiety disorders. Hum Brain Mapp 37:1178–1193, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Longitudinal changes in resting-state fMRI from age 5 to age 6years covary with language development

Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i.e., left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development.

Functional Connectivity Disruption in Neonates with Prenatal Marijuana Exposure

Prenatal marijuana exposure (PME) is linked to neurobehavioral and cognitive impairments; however, findings in childhood and adolescence are inconsistent. Type-1 cannabinoid receptors (CB1R) modulate fetal neurodevelopment, mediating PME effects on growth of functional circuitry sub-serving behaviors critical for academic and social success. The purpose of this study was to investigate the effects of prenatal marijuana on development of early brain functional circuitry prior to prolonged postnatal environmental influences. We measured resting state functional connectivity during unsedated sleep in infants at 2–6 weeks (+MJ: 20 with PME in combination with nicotine, alcohol, opiates, and/or selective serotonin reuptake inhibitors; −MJ: 23 exposed to the same other drugs without marijuana, CTR: 20 drug-free controls). Connectivity of subcortical seed regions with high fetal CB1R expression was examined. Marijuana-specific differences were observed in insula and three striatal connections: anterior insula–cerebellum, right caudate–cerebellum, right caudate–right fusiform gyrus/inferior occipital, left caudate–cerebellum. +MJ neonates had hypo-connectivity in all clusters compared with −MJ and CTR groups. Altered striatal connectivity to areas involved in visual spatial and motor learning, attention, and in fine-tuning of motor outputs involved in movement and language production may contribute to neurobehavioral deficits reported in this at-risk group. Disrupted anterior insula connectivity may contribute to altered integration of interoceptive signals with salience estimates, motivation, decision-making, and later drug use. Compared with CTRs, both +MJ and −MJ groups demonstrated hyper-connectivity of left amygdala seed with orbital frontal cortex and hypo-connectivity of posterior thalamus seed with hippocampus, suggesting vulnerability to multiple drugs in these circuits.

Network Centrality of Resting-State fMRI in Primary Angle-Closure Glaucoma Before and After Surgery

Purpose

Using voxel-wise degree centrality (DC), as measured by resting-state fMRI, we aimed to study alterations in the brain functional networks in patients with primary angle-closure glaucoma (PACG) and to reveal the plastic trajectories of surgery.

Methods

A total of 23 preoperative PACG patients (49.48 ± 14.37 years old) were recruited to undergo a resting-state fMRI scan, and 9 of them were rescanned 3 months after surgery. All PACG patients underwent a complete ophthalmologic examination, including intraocular pressure (IOP), retinal nerve fiber layer (RNFL) thickness, vertical cup to disc ratio (V C/D), and average cup to disc ratio (A C/D). Another 23 gender- and age-matched healthy controls (48.18 ± 9.40 years old) underwent scanning once for comparison. The group difference in DC was calculated in each voxel, and the correlations between the DC value and each of the clinical variables were analyzed in the PACG patients.

Results

Preoperative PACG (pre-PACG) patients showed significantly decreased DC in the bilateral visual cortices but increased DC in the left anterior cingulate cortex (ACC) and caudate (p < 0.05, corrected) compared with the controls. Statistical analysis showed a significantly negative correlation between DC in the bilateral visual cortices and the IOP score and between DC in the anterior cingulate cortex (ACC) and both the A C/D and V C/D scores in the pre-PACG patients. Three months after surgery, these postoperative PACG (post-PACG) patients showed a significantly increased DC in both the bilateral visual cortices and the left precentral gyrus compared with the pre-PACG patients.

Conclusions

Our results suggest that PACG may contribute to decreased functional centrality in the visual system and to increased degree centrality in cognition-emotional processing regions. Alterations in visual areas seem to parallel the cup to disc ratio, but not the duration of angle closure. The changes of functional centrality in PACG patients after operation may reveal the plasticity or degeneration of the visual-associated brain areas. Our findings may provide further understanding of the pathophysiology of PACG.

Resting-state functional connectivity of the default mode network associated with happiness

Happiness refers to people's cognitive and affective evaluation of their life. Why are some people happier than others? One reason might be that unhappy people are prone to ruminate more than happy people. The default mode network (DMN) is normally active during rest and is implicated in rumination. We hypothesized that unhappiness may be associated with increased default-mode functional connectivity during rest, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC) and inferior parietal lobule (IPL). The hyperconnectivity of these areas may be associated with higher levels of rumination. One hundred forty-eight healthy participants underwent a resting-state fMRI scan. A group-independent component analysis identified the DMNs. Results indicated increased functional connectivity in the DMN was associated with lower levels of happiness. Specifically, relative to happy people, unhappy people exhibited greater functional connectivity in the anterior medial cortex (bilateral MPFC), posterior medial cortex regions (bilateral PCC) and posterior parietal cortex (left IPL). Moreover, the increased functional connectivity of the MPFC, PCC and IPL, correlated positively with the inclination to ruminate. These results highlight the important role of the DMN in the neural correlates of happiness, and suggest that rumination may play an important role in people's perceived happiness.

Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchronization

The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome.

Intrinsic brain indices of verbal working memory capacity in children and adolescents

Working memory (WM) is central to the acquisition of knowledge and skills throughout childhood and adolescence. While numerous behavioral and task-based functional magnetic resonance imaging (fMRI) studies have examined WM development, few have used resting-state fMRI (R-fMRI). Here, we present a systematic R-fMRI examination of age-related differences in the neural indices of verbal WM performance in a cross-sectional pediatric sample (ages: 7-17; n=68), using data-driven approaches. Verbal WM capacity was measured with the digit span task, a commonly used educational and clinical assessment. We found distinct neural indices of digit span forward (DSF) and backward (DSB) performance, reflecting their unique neuropsychological demands. Regardless of age, DSB performance was related to intrinsic properties of brain areas previously implicated in attention and cognitive control, while DSF performance was related to areas less commonly implicated in verbal WM storage (precuneus, lateral visual areas). From a developmental perspective, DSF exhibited more robust age-related differences in brain-behavior relationships than DSB, and implicated a broader range of networks (ventral attention, default, somatomotor, limbic networks)--including a number of regions not commonly associated with verbal WM (angular gyrus, subcallosum). These results highlight the importance of examining the neurodevelopment of verbal WM and of considering regions beyond the "usual suspects".

Dorsal anterior cingulate cortex in typically developing children: Laterality analysis

We aimed to elucidate the dACC laterality in typically developing children and their sex/age-related differences with a sample of 84 right-handed children (6-16 years, 42 boys). We first replicated the previous finding observed in adults that gray matter density asymmetry in the dACC was region-specific: leftward (left > right) in its superior part, rightward (left < right) in its inferior part. Intrinsic connectivity analysis of these regions further revealed region-specific asymmetric connectivity profiles in dACC as well as their sex and age differences. Specifically, the superior dACC connectivity with frontoparietal network and the inferior dACC connectivity with visual network are rightward. The superior dACC connectivity with the default network (lateral temporal cortex) was more involved in the left hemisphere. In contrast, the inferior dACC connectivity with the default network (anterior medial prefrontal cortex) was more lateralized towards the right hemisphere. The superior dACC connectivity with lateral visual cortex was more distinct across two hemispheres in girls than that in boys. This connection in boys changed with age from right-prominent to left-prominent asymmetry whereas girls developed the connection from left-prominent to no asymmetry. These findings not only highlight the complexity and laterality of the dACC but also provided insights into dynamical structure-function relationships during the development.

Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. Early differentiation between both types of dementia may be challenging due to heterogeneity and overlap of symptoms. Here, we apply resting state functional magnetic resonance imaging (fMRI) to study functional brain connectivity differences between AD and bvFTD.

METHODS

We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls from two centers specialized in dementia. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume.

RESULTS

Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between (a) lateral visual cortical network and lateral occipital and cuneal cortex, and (b) auditory system network and angular gyrus. In AD, we found decreased network-to-region connectivity between the dorsal visual stream network and lateral occipital and parietal opercular cortex. Region-to-region connectivity was decreased in bvFTD between superior temporal gyrus and cuneal, supracalcarine, intracalcarine cortex, and lingual gyrus.

CONCLUSION

We showed that the pathophysiology of functional brain connectivity is different between AD and bvFTD. Our findings support the hypothesis that resting state fMRI shows disease-specific functional connectivity differences and is useful to elucidate the pathophysiology of AD and bvFTD. However, the group differences in functional connectivity are less abundant than has been shown in previous studies.

Development of a selective left-hemispheric fronto-temporal network for processing syntactic complexity in language comprehension

The development of language comprehension abilities in childhood is closely related to the maturation of the brain, especially the ability to process syntactically complex sentences. Recent studies proposed that the fronto-temporal connection within left perisylvian regions, supporting the processing of syntactically complex sentences, is still immature at preschool age. In the current study, resting state functional magnetic resonance imaging data were acquired from typically developing 5-year-old children and adults to shed further light on the brain functional development. Children additionally performed a behavioral syntactic comprehension test outside the scanner. The amplitude of low-frequency fluctuations was analyzed in order to identify the functional correlation networks of language-relevant brain regions. Results showed an intrahemispheric correlation between left inferior frontal gyrus (IFG) and left posterior superior temporal sulcus (pSTS) in adults, whereas an interhemispheric correlation between left IFG and its right-hemispheric homolog was predominant in children. Correlation analysis between resting-state functional connectivity and sentence processing performance in 5-year-olds revealed that local connectivity within the left IFG is associated with competence of processing syntactically simple canonical sentences, while long-range connectivity between IFG and pSTS in left hemisphere is associated with competence of processing syntactically relatively more complex non-canonical sentences. The present developmental data suggest that a selective left fronto-temporal connectivity network for processing complex syntax is already in functional connection at the age of 5 years when measured in a non-task situation. The correlational findings provide new insight into the relationship between intrinsic functional connectivity and syntactic language abilities in preschool children.

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resting state ALFF correlated in adults between left IFG and left pSTS.

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resting state ALFF correlated in children between left IFG and right homolog area.

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intrahemispheric connectivity co-varies with syntactic processing skills in children.

Short-term test-retest reliability of resting state fMRI metrics in children with and without attention-deficit/hyperactivity disorder

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Children with or without ADHD have moderate/high R-fMRI test–retest reliability.

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Reliability is greater in controls than ADHD across most R-fMRI metrics.

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Regional differences in ICC related to diagnostic groups reflect underlying pathophysiology for ADHD affecting both inter and intra subject variability.

To date, only one study has examined test–retest reliability of resting state fMRI (R-fMRI) in children, none in clinical developing groups. Here, we assessed short-term test–retest reliability in a sample of 46 children (11–17.9 years) with attention-deficit/hyperactivity disorder (ADHD) and 57 typically developing children (TDC). Our primary test–retest reliability measure was the intraclass correlation coefficient (ICC), quantified for a range of R-fMRI metrics. We aimed to (1) survey reliability within and across diagnostic groups, and (2) compare voxel-wise ICC between groups. We found moderate-to-high ICC across all children and within groups, with higher-order functional networks showing greater ICC. Nearly all R-fMRI metrics exhibited significantly higher ICC in TDC than in children with ADHD for one or more regions. In particular, posterior cingulate and ventral precuneus exhibited group differences in ICC across multiple measures. In the context of overall moderate-to-high test–retest reliability in children, regional differences in ICC related to diagnostic groups likely reflect the underlying pathophysiology for ADHD. Our currently limited understanding of the factors contributing to inter- and intra-subject variability in ADHD underscores the need for large initiatives aimed at examining their impact on test–retest reliability in both clinical and developing populations.

Global signal regression has complex effects on regional homogeneity of resting state fMRI signal

Regional homogeneity (ReHo) quantifies spatially local synchronization of resting state fMRI signal and has been applied to lots of clinic studies. Accumulating evidences demonstrated that the synchronization between spatially distinct brain regions, i.e. functional connectivity, can be remarkably influenced if the global mean time course is regressed out, namely global signal regression (GSR). Very recently, it was reported GSR reduces the test-retest reliability of ReHo, and reduces the positive correlation between ReHo and head motion. In this study, we were interested in two questions: 1) how GSR affects the raw ReHo values and its spatial distribution over the brain; 2) how GSR affects the differences of ReHo between two resting states, eyes open (EO) and eyes closed (EC), in healthy individuals. We found that the ReHo values were reduced by GSR but the spatial distribution of ReHo was not changed remarkably. In addition, split-half reproducibility analysis showed reproducible ReHo difference between EO and EC in some areas (e.g., thalamus and caudate) only with GSR, but showed reproducible ReHo difference in some other area (right temporal pole) only without GSR. The effects of GSR were almost independent of regression of other nuisance covariates. Our results suggest that the influences of GSR on ReHo are remarkable, reliable and complex. For the between-condition comparison, the GSR effects are region specific. We suggest that, for application studies using ReHo approach, it would be helpful to report results both with and without GSR.

Intrinsic functional plasticity of the sensorimotor network in relapsing-remitting multiple sclerosis: evidence from a centrality analysis

Background and Purpose

Advanced MRI studies have revealed regional alterations in the sensorimotor cortex of patients with relapsing-remitting multiple sclerosis (RRMS). However, the organizational features underlying the relapsing phase and the subsequent remitting phase have not been directly shown at the functional network or the connectome level. Therefore, this study aimed to characterize MS-related centrality disturbances of the sensorimotor network (SMN) and to assess network integrity and connectedness.

Methods

Thirty-four patients with clinically definite RRMS and well-matched healthy controls participated in the study. Twenty-three patients in the remitting phase underwent one resting-state functional MRI, and 11 patients in the relapsing-remitting phase underwent two different MRIs. We measured voxel-wise centrality metrics to determine direct (degree centrality, DC) and global (eigenvector centrality, EC) functional relationships across the entire SMN.

Results

In the relapsing phase, DC was significantly decreased in the bilateral primary motor and somatosensory cortex (M1/S1), left dorsal premotor (PMd), and operculum-integrated regions. However, DC was increased in the peripheral SMN areas. The decrease in DC in the bilateral M1/S1 was associated with the expanded disability status scale (EDSS) and total white matter lesion loads (TWMLLs), suggesting that this adaptive response is related to the extent of brain damage in the rapid-onset attack stage. During the remission process, these alterations in centrality were restored in the bilateral M1/S1 and peripheral SMN areas. In the remitting phase, DC was reduced in the premotor, supplementary motor, and operculum-integrated regions, reflecting an adaptive response due to brain atrophy. However, DC was enhanced in the right M1 and left parietal-integrated regions, indicating chronic reorganization. In both the relapsing and remitting phases, the changes in EC and DC were similar.

Conclusions

The alterations in centrality within the SMN indicate rapid plasticity and chronic reorganization with a biased impairment of specific functional areas in RRMS patients.

Neural Correlates of Associative Memory in the Elderly: A Resting-State Functional MRI Study

The neural correlates of associative memory in healthy older adults were investigated by examining the correlation of associative memory performance with spontaneous brain oscillations. Eighty healthy older adults underwent a resting-state functional MRI and took a paired-associative learning test (PALT). Correlations between the amplitude of low-frequency fluctuations (ALFF) as well as fractional ALFF (fALFF) in the whole brain and PALT scores were calculated. We found that spontaneous activity as indexed by both ALFF and fALFF in the parahippocampal gyrus (PHG) was significantly positively correlated with associative memory performance, suggesting that the PHG plays a critical role in associative memory in older people.

Local-to-remote cortical connectivity in early- and adulthood-onset schizophrenia

Schizophrenia is increasingly thought of as a brain network or connectome disorder and is associated with neurodevelopmental processes. Previous studies have suggested the important role of anatomical distance in developing a connectome with optimized performance regarding both the cost and efficiency of information processing. Distance-related disturbances during development have not been investigated in schizophrenia. To test the distance-related miswiring profiles of connectomes in schizophrenia, we acquired resting-state images from 20 adulthood-onset (AOS) and 26 early-onset schizophrenia (EOS) patients, as well as age-matched healthy controls. All patients were drug naive and had experienced their first psychotic episode. A novel threshold-free surface-based analytic framework was developed to examine local-to-remote functional connectivity profiles in both AOS and EOS patients. We observed consistent increases of local connectivity across both EOS and AOS patients in the right superior frontal gyrus, where the connectivity strength was correlated with a positive syndrome score in AOS patients. In contrast, EOS but not AOS patients exhibited reduced local connectivity within the right postcentral gyrus and the left middle occipital cortex. These regions' remote connectivity with their interhemispheric areas and brain network hubs was altered. Diagnosis-age interactions were detectable for both local and remote connectivity profiles. The functional covariance between local and remote homotopic connectivity was present in typically developing controls, but was absent in EOS patients. These findings suggest that a distance-dependent miswiring pattern may be one of the key neurodevelopmental features of the abnormal connectome organization in schizophrenia.

Intrinsic functional plasticity of the sensory-motor network in patients with cervical spondylotic myelopathy

Several neuroimaging studies have suggested brain reorganisation in patients with cervical spondylotic myelopathy (CSM); however, the changes in spontaneous neuronal activity that are associated with connectedness remain largely unknown. In this study, functional connectivity strength (FCS), a data-driven degree centrality method based on a theoretical approach, was applied for the first time to investigate changes in the sensory-motor network (SMN) at the voxel level. Comparatively, CSM not only showed significantly decreased FCS in the operculum-integrated regions, which exhibited reduced resting-state functional connectivity (rsFC) around the Rolandic sulcus, but it also showed increased FCS in the premotor, primary somatosensory, and parietal-integrated areas, which primarily showed an enhanced rsFC pattern. Correlation analysis showed that altered FCS (in the left premotor-ventral/precentral-operculum, right operculum-parietale 4, and right S1) was associated with worsening Japanese Orthopaedic Association scores and that the rsFC pattern was influenced by cervical cord micro-structural damage at the C2 level. Together, these findings suggest that during myelopathy, the intrinsic functional plasticity of the SMN responds to the insufficient sensory and motor experience in CSM patients. This knowledge may improve our understanding of the comprehensive functional defects found in CSM patients and may inspire the development of new therapeutic strategies in the future.

An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data

Large amounts of multimodal neuroimaging data are acquired every year worldwide. In order to extract high-dimensional information for computational neuroscience applications standardized data fusion and efficient reduction into integrative data structures are required. Such self-consistent multimodal data sets can be used for computational brain modeling to constrain models with individual measurable features of the brain, such as done with The Virtual Brain (TVB). TVB is a simulation platform that uses empirical structural and functional data to build full brain models of individual humans. For convenient model construction, we developed a processing pipeline for structural, functional and diffusion-weighted magnetic resonance imaging (MRI) and optionally electroencephalography (EEG) data. The pipeline combines several state-of-the-art neuroinformatics tools to generate subject-specific cortical and subcortical parcellations, surface-tessellations, structural and functional connectomes, lead field matrices, electrical source activity estimates and region-wise aggregated blood oxygen level dependent (BOLD) functional MRI (fMRI) time-series. The output files of the pipeline can be directly uploaded to TVB to create and simulate individualized large-scale network models that incorporate intra- and intercortical interaction on the basis of cortical surface triangulations and white matter tractograpy. We detail the pitfalls of the individual processing streams and discuss ways of validation. With the pipeline we also introduce novel ways of estimating the transmission strengths of fiber tracts in whole-brain structural connectivity (SC) networks and compare the outcomes of different tractography or parcellation approaches. We tested the functionality of the pipeline on 50 multimodal data sets. In order to quantify the robustness of the connectome extraction part of the pipeline we computed several metrics that quantify its rescan reliability and compared them to other tractography approaches. Together with the pipeline we present several principles to guide future efforts to standardize brain model construction. The code of the pipeline and the fully processed data sets are made available to the public via The Virtual Brain website (thevirtualbrain.org) and via github (https://github.com/BrainModes/TVB-empirical-data-pipeline). Furthermore, the pipeline can be directly used with High Performance Computing (HPC) resources on the Neuroscience Gateway Portal (http://www.nsgportal.org) through a convenient web-interface.

Detecting static and dynamic differences between eyes-closed and eyes-open resting states using ASL and BOLD fMRI

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain.

Frequency-dependent changes of local resting oscillations in sleep-deprived brain

Sleep deprivation (SD) adversely affects brain function and is accompanied by frequency dependent changes in EEG. Recent studies have suggested that BOLD fluctuations pertain to a spatiotemporal organization with different frequencies. The present study aimed to investigate the frequency-dependent SD-related brain oscillatory activity by using the amplitude of low-frequency fluctuation (ALFF) analysis. The ALFF changes were measured across different frequencies (Slow-4: 0.027–0.073 Hz; Slow-5: 0.01–0.027 Hz; and Typical band: 0.01–0.08 Hz) in 24 h SD as compared to rested wakeful during resting-state fMRI. Sixteen volunteers underwent two fMRI sessions, once during rested wakefulness and once after 24 h of SD. SD showed prominently decreased ALFF in the right inferior parietal lobule (IPL), bilateral orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC), while increased ALFF in the visual cortex, left sensorimotor cortex and fusiform gyrus. Across the Slow-4 and Slow-5, results differed significantly in the OFC, DLPFC, thalamus and caudate in comparison to typical frequency band; and Slow-4 showed greater differences. In addition, negative correlations of behavior performance and ALFF patterns were found mainly in the right IPL across the typical frequency band. These observations provided novel insights about the physiological responses of SD, identified how it disturbs the brain rhythms, and linked SD with frequency-dependent alterations in amplitude patterns.