Functional coactivation map of the human brain

Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains

Human brain anatomical and resting-state functional connectivity have been comprehensively portrayed using MRI, which are termed anatomical and functional connectomes. A systematic examination of tasks modulated whole brain functional connectivity, which we term as task connectome, is still lacking. We analyzed 6 block-designed and 1 event-related designed functional MRI data, and examined whole-brain task modulated connectivity in various task domains, including emotion, reward, language, relation, social cognition, working memory, and inhibition. By using psychophysiological interaction between pairs of regions from the whole brain, we identified statistically significant task modulated connectivity in 4 tasks between their experimental and respective control conditions. Task modulated connectivity was found not only between regions that were activated during the task but also regions that were not activated or deactivated, suggesting a broader involvement of brain regions in a task than indicated by simple regional activations. Decreased functional connectivity was observed in all the 4 tasks and sometimes reduced connectivity was even between regions that were both activated during the task. This suggests that brain regions that are activated together do not necessarily work together. The current study demonstrates the comprehensive task connectomes of 4 tasks, and suggested complex relationships between regional activations and connectivity changes.

Forced conceptual thought induced by electrical stimulation of the left prefrontal gyrus involves widespread neural networks

BACKGROUND

Early accounts of forced thought were reported at the onset of a focal seizure, and characterized as vague, repetitive, and involuntary intellectual auras distinct from perceptual or psychic hallucinations or illusions. Here, we examine the neural underpinnings involved in conceptual thought by presenting a series of 3 patients with epilepsy reporting intrusive thoughts during electrical stimulation of the left lateral prefrontal cortex (PFC) during invasive surgical evaluation. We illustrate the widespread networks involved through two independent brain imaging modalities: resting state functional magnetic resonance imaging (fMRI) (rs-fMRI) and task-based meta-analytic connectivity modeling (MACM).

METHODS

We report the clinical and stimulation characteristics of three patients with left hemispheric language dominance who demonstrate forced thought with functional mapping. To examine the brain networks underlying this phenomenon, we used the regions of interest (ROI) centered at the active electrode pairs. We modeled functional networks using two approaches: (1) rs-fMRI functional connectivity analysis, representing 81 healthy controls and (2) meta-analytic connectivity modeling (MACM), representing 8260 healthy subjects. We also determined the overlapping regions between these three subjects' rs-fMRI and MACM networks through a conjunction analysis.

RESULTS

We identified that left PFC was associated with a large-scale functional network including frontal, temporal, and parietal regions, a network that has been associated with multiple cognitive functions including semantics, speech, attention, working memory, and explicit memory.

CONCLUSIONS

We illustrate the neural networks involved in conceptual thought through a unique patient population and argue that PFC supports this function through activation of a widespread network.

Modified models and simulations for estimating dynamic functional connectivity in resting state functional magnetic resonance imaging

As understanding the nature of brain networks through dynamic functional connectivity (dFC) estimation is of paramount significant, the introduction and revision of blood-oxygen-level dependent (BOLD) signal simulation methods in brain regions and dFC estimation methods have gained significant ground in recent years. Based on the observation of BOLD signals with multivariate nonnormal distribution in functional magnetic resonance imaging (fMRI) images, we first propose a copula-based method for the production of these signals, in which nonnormal data are generated with a selected time-varying covariance matrix. Therefore, we can compare the performance of models in the cases where brain signals have a multivariate nonnormal distribution. Then, two kendallized exponentially weighted moving average (KEWMA) and kendallized dynamic conditional correlation (KDCC) multivariate volatility models are introduced which are based on two well-known and commonly used exponentially weighted moving average (EMWA) and dynamic conditional correlation (DCC) models. The results show that KDCC model can estimate conditional correlation significantly far better than the former ones (ie, DCC, standardized dynamic conditional correlation, EWMA, and standardized exponentially weighted moving average) on both types of data (ie, multivariate normal and nonnormal). In the next step, the bivariate normal distribution in Iranian resting state fMRI data is confirmed by using statistical tests, and it is shown that the dynamic nature of FC is not optimally detected using prevalent methods. Two alternative Portmanteau and rank-based tests are proposed for the examination of conditional heteroscedasticity in data. Finally, dFC in these data is estimated by employing the KDCC model.

Ontological Dimensions of Cognitive-Neural Mappings

The growing literature reporting results of cognitive-neural mappings has increased calls for an adequate organizing ontology, or taxonomy, of these mappings. This enterprise is non-trivial, as relevant dimensions that might contribute to such an ontology are not yet agreed upon. We propose that any candidate dimensions should be evaluated on their ability to explain observed differences in functional neuroimaging activation patterns. In this study, we use a large sample of task-based functional magnetic resonance imaging (task-fMRI) results and a data-driven strategy to identify these dimensions. First, using a data-driven dimension reduction approach and multivariate distance matrix regression (MDMR), we quantify the variance among activation maps that is explained by existing ontological dimensions. We find that 'task paradigm' categories explain more variance among task-activation maps than other dimensions, including latent cognitive categories. Surprisingly, 'study ID', or the study from which each activation map was reported, explained close to 50% of the variance in activation patterns. Using a clustering approach that allows for overlapping clusters, we derived data-driven latent activation states, associated with re-occurring configurations of the canonical frontoparietal, salience, sensory-motor, and default mode network activation patterns. Importantly, with only four data-driven latent dimensions, one can explain greater variance among activation maps than all conventional ontological dimensions combined. These latent dimensions may inform a data-driven cognitive ontology, and suggest that current descriptions of cognitive processes and the tasks used to elicit them do not accurately reflect activation patterns commonly observed in the human brain.

Aberrant interhemispheric functional connectivity in first-episode, drug-naïve major depressive disorder

Many studies have indicated that depression is associated with impairment of the topological organization of the brain functional network, which may lead to disruption of mood and cognition in depressive patients. The abnormality of homotopic connectivity provides a basis for the clinical manifestations of depression, such as emotional and cognitive disorders. Several studies have investigated the abnormal imbalance of homotopic regions between the hemispheres in depressive patients. However, the reported findings are inconsistent. Additionally, the published studies have focused on only the grey matter when investigating functional connectivity abnormalities of the bilateral cerebral hemispheres in major depressive disorder (MDD). The aim of this study is to investigate functional connectivity abnormalities of the bilateral cerebral hemispheres in patients with first-episode, drug-naïve MDD using a voxel-mirrored homotopic connectivity (VMHC) method. Based on DSM-IV diagnostic criteria, 23 first-episode, drug-naïve MDD patients were recruited, together with 20 gender- and age-matched healthy normal controls. A Philips Achieva 3.0 T MRI scanner was used to acquire brain functional images at resting state as well as high-resolution structural images. The functional images were preprocessed by using Data Processing Assistant for Resting-State Functional MR Imaging toolkit and SPM8.VMHC between the bilateral hemispheres was computed and compared between the MDD and control groups. The correlation between the VMHC values of the abnormal homotopy function areas and the Hamilton Depression Rating Scale (HAMD) was evaluated in the MDD patients. Compared with the control group, the MDD patients showed significantly decreased VMHC values in the bilateral brain regions including the insular, putamen, and frontal white matter. The MDD patients did not exhibit increased VMHC values in any brain regions compared with the normal controls. In addition, a negative correlation was observed between the VMHC value in the frontal lobe white-matter and the HAMD in the MDD patients. Abnormalities in brain homotopic functional connectivity observed in this study may indicate abnormal neural circuits related to aberrant cognition and emotional processing in MDD. Although the physiological significance underlaying abnormal VMHC in white matter in the frontal lobe needs further research, our study new angle to investigate the role of white-matter abnormalities in MDD as well as other psychiatric disorders.

Alterations of connectivity patterns in functional brain networks in patients with mild traumatic brain injury: A longitudinal resting-state functional magnetic resonance imaging study

AIM

In the present study, we aimed to characterise changes in functional brain networks in individuals who had sustained uncomplicated mild traumatic brain injury (mTBI). We assessed the progression of these changes into the chronic phase. We also attempted to explore how these changes influenced the severity of post-concussion symptoms as well as the cognitive profile of the patients.

METHODS

A total of 65 patients were prospectively recruited for an advanced magnetic resonance imaging (MRI) scan within 7 days of sustaining mTBI. Of these, 25 were reassessed at 6 months post injury. Differences in functional brain networks were analysed between cases and age- and sex-matched healthy controls using independent component analysis of resting-state functional MRI.

RESULTS

Our study revealed reduced functional connectivity in multiple networks, including the anterior default mode network, central executive network, somato-motor and auditory network in patients who had sustained mTBI. A negative correlation between network connectivity and severity of post-concussive symptoms was observed. Follow-up studies performed 6 months after injury revealed an increase in network connectivity, along with an improvement in the severity of post-concussion symptoms. Neurocognitive tests performed at this time point revealed a positive correlation between the functional connectivity and the test scores, along with a persistence of negative correlation between network connectivity and post-concussive symptom severity.

CONCLUSION

Our results suggest that uncomplicated mTBI is associated with specific abnormalities in functional brain networks that evolve over time and may contribute to the severity of post-concussive symptoms and cognitive deficits.

Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks

The past decade has witnessed a proliferation of studies aimed at characterizing the human connectome. These projects map the brain regions comprising large-scale systems underlying cognition using non-invasive neuroimaging approaches and advanced analytic techniques adopted from network science. While the idea that the human brain is composed of multiple macro-scale functional networks has been gaining traction in cognitive neuroscience, the field has yet to reach consensus on several key issues regarding terminology. What constitutes a functional brain network? Are there "core" functional networks, and if so, what are their spatial topographies? What naming conventions, if universally adopted, will provide the most utility and facilitate communication amongst researchers? Can a taxonomy of functional brain networks be delineated? Here we survey the current landscape to identify six common macro-scale brain network naming schemes and conventions utilized in the literature, highlighting inconsistencies and points of confusion where appropriate. As a minimum recommendation upon which to build, we propose that a scheme incorporating anatomical terminology should provide the foundation for a taxonomy of functional brain networks. A logical starting point in this endeavor might delineate systems that we refer to here as "occipital", "pericentral", "dorsal frontoparietal", "lateral frontoparietal", "midcingulo-insular", and "medial frontoparietal" networks. We posit that as the field of network neuroscience matures, it will become increasingly imperative to arrive at a taxonomy such as that proposed here, that can be consistently referenced across research groups.

Large-scale Meta-analysis Suggests Low Regional Modularity in Lateral Frontal Cortex

Extensive fMRI study of human lateral frontal cortex (LFC) has yet to yield a consensus mapping between discrete anatomy and psychological states, partly due to the difficulty of inferring mental states from brain activity. Despite this, there have been few large-scale efforts to map the full range of psychological states across the entirety of LFC. Here, we used a data-driven approach to generate a comprehensive functional-anatomical mapping of LFC from 11 406 neuroimaging studies. We identified putatively separable LFC regions on the basis of whole-brain co-activation, revealing 14 clusters organized into 3 whole-brain networks. Next, we generated functional preference profiles by using multivariate classification to identify the psychological states that best predicted activity within each cluster. We observed large functional differences between networks, suggesting brain networks support distinct modes of processing. Within each network, however, we observed relatively low functional specificity, suggesting discrete psychological states are not strongly localized to individual regions; instead, our results are consistent with the view that individual LFC regions work as part of distributed networks to give rise to flexible behavior. Collectively, our results provide a comprehensive synthesis of a diverse neuroimaging literature using relatively unbiased data-driven methods.

Focal epilepsy caused by single cerebral cavernous malformation (CCM) is associated with regional and global resting state functional connectivity (FC) disruption

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To our knowledge, this is the first study to report resting state functional connectivity (FC) abnormalities associated with focal epilepsy caused by a single cerebral cavernous malformation (CCM).

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We show, by comparing to the data acquired from the age and gender matched control group, that this type of focal epilepsy is associated with the disruption of the normal regional and global FC. The disruption includes a decrease in the coactivation between the region surrounding the CCM lesion, i.e., the lesional region, and its homotopic counterpart, a reduction in FC between the lesional region and the rest of the brain, and decreased FC among the default mode network (DMN).

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These changes may be alleviated or reversed after the surgical resection of the CCM and the epileptogenic zone has successfully stopped recurrent seizures.

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Finally, the severity of the FC disruption in the brain tissue adjacent to the CCM may be used to delineate the epileptogenic zone and to aid the surgical resection.

Epilepsy, including the type with focal onset, is increasingly viewed as a disorder of the brain network. Here we employed the functional connectivity (FC) metrics estimated from the resting state functional MRI (rsfMRI) to investigate the changes of brain network associated with focal epilepsy caused by single cerebral cavernous malformation (CCM). Eight CCM subjects and 21 age and gender matched controls were enrolled in the study. Seven of 8 CCM subjects underwent surgical resection of the CCM and became seizure free and 4 of the surgical subjects underwent a repeat rsfMRI study. We showed that there was both regional and global disruption of the FC values among the CCM subjects including decreased in homotopic FC (HFC) and global FC (GFC) in the regions of interest (ROIs) where the CCMs were located. There was also the disruption of the default mode network (DMN) especially the FC between the middle prefrontal cortex (MPFC) and the right lateral parietal cortex (LPR) among these individuals. We observed the trend of alleviation of these disruptions after the individual has become seizure free from the surgical resection of the CCM. Using a voxel-based approach, we found the disruption of the HFC and GFC in the brain tissue immediately adjacent to the CCM and the severity of the disruption appeared inversely proportional to the distance of the brain tissue to the lesion. Our findings confirm the disruption of normal brain networks from focal epilepsy, a process that may be reversible with successful surgical treatments rendering patients seizure free. Some voxel-based metrics may help identify the epileptogenic zone and guide the surgical resection.

Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis

Coordinate-based meta-analysis can provide important insights into mind-brain relationships. A popular approach for curated small-scale meta-analysis is activation likelihood estimation (ALE), which identifies brain regions consistently activated across a selected set of experiments, such as within a functional domain or mental disorder. ALE can also be utilized in meta-analytic co-activation modeling (MACM) to identify brain regions consistently co-activated with a seed region. Therefore, ALE aims to find consensus across experiments, treating heterogeneity across experiments as noise. However, heterogeneity within an ALE analysis of a functional domain might indicate the presence of functional sub-domains. Similarly, heterogeneity within a MACM analysis might indicate the involvement of a seed region in multiple co-activation patterns that are dependent on task contexts. Here, we demonstrate the use of the author-topic model to automatically determine if heterogeneities within ALE-type meta-analyses can be robustly explained by a small number of latent patterns. In the first application, the author-topic modeling of experiments involving self-generated thought (N = 179) revealed cognitive components fractionating the default network. In the second application, the author-topic model revealed that the left inferior frontal junction (IFJ) participated in multiple task-dependent co-activation patterns (N = 323). Furthermore, the author-topic model estimates compared favorably with spatial independent component analysis in both simulation and real data. Overall, the results suggest that the author-topic model is a flexible tool for exploring heterogeneity in ALE-type meta-analyses that might arise from functional sub-domains, mental disorder subtypes or task-dependent co-activation patterns. Code for this study is publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/meta-analysis/Ngo2019_AuthorTopic).

Task-evoked Negative BOLD Response and Functional Connectivity in the Default Mode Network are Representative of Two Overlapping but Separate Neurophysiological Processes

The topography of the default mode network (DMN) can be obtained with one of two different functional magnetic resonance imaging (fMRI) methods: either from the spontaneous but organized synchrony of the low-frequency fluctuations in resting-state fMRI (rs-fMRI), known as "functional connectivity", or from the consistent and robust deactivations in task-based fMRI (tb-fMRI), here referred to as the "negative BOLD response" (NBR). These two methods are fundamentally different, but their results are often used interchangeably to describe the brain's resting-state, baseline, or intrinsic activity. While the DMN was initially defined by consistent task-based decreases in blood flow in a set of specific brain regions using PET imaging, recently nearly all studies on the DMN employ functional connectivity in rs-fMRI. In this study, we first show the high level of spatial overlap between NBR and functional connectivity of the DMN extracted from the same tb-fMRI scan; then, we demonstrate that the NBR in putative DMN regions can be significantly altered without causing any change in their overlapping functional connectivity. Furthermore, we present evidence that in the DMN, the NBR is more closely related to task performance than the functional connectivity. We conclude that the NBR and functional connectivity of the DMN reflect two separate but overlapping neurophysiological processes, and thus should be differentiated in studies investigating brain-behavior relationships in both healthy and diseased populations. Our findings further raise the possibility that the macro-scale networks of the human brain might internally exhibit a hierarchical functional architecture.

Brain structural alterations are distributed following functional, anatomic and genetic connectivity

The pathological brain is characterized by distributed morphological or structural alterations in the grey matter, which tend to follow identifiable network-like patterns. We analysed the patterns formed by these alterations (increased and decreased grey matter values detected with the voxel-based morphometry technique) conducting an extensive transdiagnostic search of voxel-based morphometry studies in a large variety of brain disorders. We devised an innovative method to construct the networks formed by the structurally co-altered brain areas, which can be considered as pathological structural co-alteration patterns, and to compare these patterns with three associated types of connectivity profiles (functional, anatomical, and genetic). Our study provides transdiagnostical evidence that structural co-alterations are influenced by connectivity constraints rather than being randomly distributed. Analyses show that although all the three types of connectivity taken together can account for and predict with good statistical accuracy, the shape and temporal development of the co-alteration patterns, functional connectivity offers the better account of the structural co-alteration, followed by anatomic and genetic connectivity. These results shed new light on the possible mechanisms at the root of neuropathological processes and open exciting prospects in the quest for a better understanding of brain disorders.

Effects of Second Language Learning on the Plastic Aging Brain: Functional Connectivity, Cognitive Decline, and Reorganization

Learning a new language requires the use of extensive neural networks and can represent a powerful tool to reorganize brain neuroplasticity. In this study, we analyze how a 4 months long second language learning program (16, 2 h sessions) can lead to functional changes in the brain of healthy elderly individuals. A large number of studies point out a decline of brain-skills with age; here it is analyzed how cognition together with functional brain organization can be improved later in life. Twenty-six older adults (59-79 years old) were enrolled in the present study. A complete neuropsychological examination was administered before and after the intervention to measure global cognition levels, short- and long-term memory, attention, language access and executive functions. At the end of the program, in the intervention group, the results showed a significant improvement in global cognition together with an increased functional connectivity in the right inferior frontal gyrus (rIFG), right superior frontal gyrus (rSFG) and left superior parietal lobule (lSPL). These findings can be added to the current neurobiological breakthroughs of reshaping brain networks with a short language learning practice in healthy elderly subjects. Therefore, learning a foreign-language may represent a potentially helpful cognitive intervention for promoting healthy aging.

Large-scale network interactions involved in dividing attention between the external environment and internal thoughts to pursue two distinct goals

Previous research suggests that default-mode network (DMN) and dorsal attention network (DAN) are involved in internally- and externally-directed attention, respectively, through interactions with salience network (SN) and frontoparietal network (FPCN). Performing a task requiring external attention is often accompanied by a down-regulation of attention to internal thoughts, and vice-versa. In contrast, we often divide our attention between the external environment and internal thoughts to pursue distinct goals, yet virtually no prior research has examined how brain networks support this functionally critical neurocognitive process. In the current study, participants planned their responses for an upcoming alternate uses divergent thinking task (AUT-Condition), indicated whether arrows were pointing left or right (Arrows-Condition) or performed both tasks simultaneously (Dual-Task condition). Behaviorally, the Dual-Task condition was associated with equivalent generation of alternate uses but increased RT variability compared to the single-task conditions. Static connectivity analyses indicated that FPCN and SN increased their connectivity to DMN and reduced their connectivity to DAN during the Dual-Task condition and the AUT-Condition compared to the Arrows-Condition. Furthermore, DAN-SN connectivity was highest during the Arrows-Condition, intermediate during the Dual-Task condition and lowest during the AUT-Condition. Finally, time-varying connectivity analyses indicated that individuals who reported spending less time thinking of alternate uses during the Dual-Task condition spent more time in a state associated with performing the Arrows-Condition. Overall, our results suggest that interactions between DMN, FPCN, SN and DAN allow internal-external dual-tasking, and that time-varying functional connectivity between these networks is sensitive to attentional fluctuations between tasks during dual-tasking.

Local-to-distant development of the cerebrocerebellar sensorimotor network in the typically developing human brain: a functional and diffusion MRI study

Sensorimotor function is a fundamental brain function in humans, and the cerebrocerebellar circuit is essential to this function. In this study, we demonstrate how the cerebrocerebellar circuit develops both functionally and anatomically from childhood to adulthood in the typically developing human brain. We measured brain activity using functional magnetic resonance imaging while a total of 57 right-handed, blindfolded, healthy children (aged 8-11 years), adolescents (aged 12-15 years), and young adults (aged 18-23 years) (n = 19 per group) performed alternating extension-flexion movements of their right wrists in precise synchronization with 1-Hz audio tones. We also collected their diffusion MR images to examine the extent of fiber maturity in cerebrocerebellar afferent and efferent tracts by evaluating the anisotropy-sensitive index of hindrance modulated orientational anisotropy (HMOA). During the motor task, although the ipsilateral cerebellum and the contralateral primary sensorimotor cortices were consistently activated across all age groups, the functional connectivity between these two distant regions was stronger in adults than in children and adolescents, whereas connectivity within the local cerebellum was stronger in children and adolescents than in adults. The HMOA values in cerebrocerebellar afferent and efferent tracts were higher in adults than in children (some were also higher than in adolescents). The results indicate that adult-like cerebrocerebellar functional coupling is not completely achieved during childhood and adolescence, even for fundamental sensorimotor brain function, probably due to anatomical immaturity of cerebrocerebellar tracts. This study clearly demonstrated the principle of "local-to-distant" development of functional brain networks in the human cerebrocerebellar sensorimotor network.

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments.

The homotopic connectivity of the functional brain: a meta-analytic approach

Homotopic connectivity (HC) is the connectivity between mirror areas of the brain hemispheres. It can exhibit a marked and functionally relevant spatial variability, and can be perturbed by several pathological conditions. The voxel-mirrored homotopic connectivity (VMHC) is a technique devised to enquire this pattern of brain organization, based on resting state functional connectivity. Since functional connectivity can be revealed also in a meta-analytical fashion using co-activations, here we propose to calculate the meta-analytic homotopic connectivity (MHC) as the meta-analytic counterpart of the VMHC. The comparison between the two techniques reveals their general similarity, but also highlights regional differences associated with how HC varies from task to rest. Two main differences were found from rest to task: (i) regions known to be characterized by global hubness are more similar than regions displaying local hubness; and (ii) medial areas are characterized by a higher degree of homotopic connectivity, while lateral areas appear to decrease their degree of homotopic connectivity during task performance. These findings show that MHC can be an insightful tool to study how the hemispheres functionally interact during task and rest conditions.

An average sliding window correlation method for dynamic functional connectivity

Sliding window correlation (SWC) is utilized in many studies to analyze the temporal characteristics of brain connectivity. However, spurious artifacts have been reported in simulated data using this technique. Several suggestions have been made through the development of the SWC technique. Recently, it has been proposed to utilize a SWC window length of 100 s given that the lowest nominal fMRI frequency is 0.01 Hz. The main pitfall is the loss of temporal resolution due to a large window length. In this work, we propose an average sliding window correlation (ASWC) approach that presents several advantages over the SWC. One advantage is the requirement for a smaller window length. This is important because shorter lengths allow for a more accurate estimation of transient dynamicity of functional connectivity. Another advantage is the behavior of ASWC as a tunable high pass filter. We demonstrate the advantages of ASWC over SWC using simulated signals with configurable functional connectivity dynamics. We present analytical models explaining the behavior of ASWC and SWC for several dynamic connectivity cases. We also include a real data example to demonstrate the application of the new method. In summary, ASWC shows lower artifacts and resolves faster transient connectivity fluctuations, resulting in a lower mean square error than in SWC.

Aberrant "deep connectivity" in autism: A cortico-subcortical functional connectivity magnetic resonance imaging study

The number of studies examining functional brain networks in Autism Spectrum Disorder (ASD) has risen over the last decade and has characterized ASD as a disorder of altered brain connectivity. However, these studies have focused largely on cortical structures, and only a few studies have examined cortico-subcortical connectivity in regions like thalamus and basal ganglia in ASD. The goal of this study was to characterize the functional connectivity between cortex and subcortical regions in ASD using the Autism Brain Imaging Data Exchange (ABIDE-II). Resting-state functional magnetic resonance imaging data were used from 168 typically developing (TD) and 138 ASD participants across different sites from the ABIDE II dataset. Functional connectivity of basal ganglia and thalamus to unimodal and supramodal networks was examined in this study. Overconnectivity (ASD > TD) was found between unimodal (except for medial visual network) and subcortical regions, and underconnectivity (TD > ASD) was found between supramodal (except for default mode and dorsal attention networks) and subcortical regions; positive correlations between ASD phenotype and unimodal-subcortical connectivity were found and negative ones with supramodal-subcortical connectivity. These findings suggest that brain networks heavily involved in sensory processing had higher connectivity with subcortical regions, whereas those involved in higher-order thinking showed decreased connectivity in ASD. In addition, brain-behavior correlations indicated a relationship between ASD phenotype and connectivity. Thus, differences in cortico-subcortical connectivity may have a significant impact on basic and higher-order cognitive processes in ASD. Autism Res 2019, 12: 384-400 © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study focused on examining the functional connectivity (synchronization of brain activity across regions) of two types of brain networks (unimodal and supramodal) with subcortical areas (thalamus and basal ganglia) in children, adolescents, and adults with autism spectrum disorder (ASD) and how this relates to ASD phenotype. ASD participants showed overconnectivity in unimodal networks and underconnectivity in supramodal networks. These findings provide new insights into cortico-subcortical connections between basic sensory and high-order cognitive processes.

Disrupted Resting Frontal-Parietal Attention Network Topology Is Associated With a Clinical Measure in Children With Attention-Deficit/Hyperactivity Disorder

Purpose: Although alterations in resting-state functional connectivity between brain regions have been reported in children with attention-deficit/hyperactivity disorder (ADHD), the spatial organization of these changes remains largely unknown. Here, we studied frontal-parietal attention network topology in children with ADHD, and related topology to a clinical measure of disease progression. Methods: Resting-state fMRI scans were obtained from New York University Child Study Center, including 119 children with ADHD (male n = 89; female n = 30) and 69 typically developing controls (male n = 33; female n = 36). We characterized frontal-parietal functional networks using standard graph analysis (clustering coefficient and shortest path length) and the construction of a minimum spanning tree, a novel approach that allows a unique and unbiased characterization of brain networks. Results: Clustering coefficient and path length in the frontal-parietal attention network were similar in children with ADHD and typically developing controls; however, diameter was greater and leaf number, tree hierarchy, and kappa were lower in children with ADHD, and were significantly correlated with ADHD symptom score. There were significant alterations in nodal eccentricity in children with ADHD, involving prefrontal and occipital cortex regions, which are compatible with the results of previous ADHD studies. Conclusions: Our results indicate the tendency to deviate from a more centralized organization (star-like topology) towards a more decentralized organization (line-like topology) in the frontal-parietal attention network of children with ADHD. This represents a more random network that is associated with impaired global efficiency and network decentralization. These changes appear to reflect clinically relevant phenomena and hold promise as markers of disease progression.

Explaining the neural activity distribution associated with discrete movement sequences: Evidence for parallel functional systems

To explore the effects of practice we scanned participants with fMRI while they were performing four-key unfamiliar and familiar sequences, and compared the associated activities relative to simple control sequences. On the basis of a recent cognitive model of sequential motor behavior (C-SMB), we propose that the observed neural activity would be associated with three functional networks that can operate in parallel and that allow (a) responding to stimuli in a reaction mode, (b) sequence execution using spatial sequence representations in a central-symbolic mode, and (c) sequence execution using motor chunk representations in a chunking mode. On the basis of this model and findings in the literature, we predicted which neural areas would be active during execution of the unfamiliar and familiar keying sequences. The observed neural activities were largely in line with our predictions, and allowed functions to be attributed to the active brain areas that fit the three above functional systems. The results corroborate C-SMB’s assumption that at advanced skill levels the systems executing motor chunks and translating key-specific stimuli are racing to trigger individual responses. They further support recent behavioral indications that spatial sequence representations continue to be used.

Development of human electrophysiological brain networks

Functional activity in the human brain is intrinsically organized into independently active, connected brain regions. These networks include sensorimotor systems, as well as higher-order cognitive networks such as the default mode network (DMN), which dominates activity when the brain is at rest, and the frontoparietal (FPN) and salience (SN) networks, which are often engaged during demanding tasks. Evidence from functional magnetic resonance imaging (fMRI) suggests that although sensory systems are mature by the end of childhood, the integrity of the FPN and SN develops throughout adolescence. There has been little work to corroborate these findings with electrophysiology. Using magnetoencephalography (MEG) recordings of 48 participants (aged 9–25 yr) at rest, we find that beta-band functional connectivity within the FPN, SN, and DMN continues to increase through adolescence, whereas connectivity in the visual system is mature by late childhood. In contrast to fMRI results, but replicating the MEG findings of Schäfer et al. (Schäfer CB, Morgan BR, Ye AX, Taylor MJ, Doesburg SM. Hum Brain Mapp 35: 5249–5261, 2014), we also see that connectivity between networks increases rather than decreases with age. This suggests that the development of coordinated beta-band oscillations within and between higher-order cognitive networks through adolescence might contribute to the developing abilities of adolescents to focus their attention and coordinate diverse aspects of mental activity.

NEW & NOTEWORTHY Using magnetoencephalography to assess beta frequency oscillations, we show that functional connectivity within higher-order cognitive networks increases from childhood, reaching adult values by age 20 yr. In contrast, connectivity within a primary sensory (visual) network reaches adult values by age 14 yr. In contrast to functional MRI findings, connectivity between cognitive networks matures at a rate similar to within-network connectivity, suggesting that coordination of beta oscillations both within and between networks is associated with maturation of cognitive skills.

A robust dissociation among the language, multiple demand, and default mode networks: Evidence from inter-region correlations in effect size

Complex cognitive processes, including language, rely on multiple mental operations that are carried out by several large-scale functional networks in the frontal, temporal, and parietal association cortices of the human brain. The central division of cognitive labor is between two fronto-parietal bilateral networks: (a) the multiple demand (MD) network, which supports executive processes, such as working memory and cognitive control, and is engaged by diverse task domains, including language, especially when comprehension gets difficult; and (b) the default mode network (DMN), which supports introspective processes, such as mind wandering, and is active when we are not engaged in processing external stimuli. These two networks are strongly dissociated in both their functional profiles and their patterns of activity fluctuations during naturalistic cognition. Here, we focus on the functional relationship between these two networks and a third network: (c) the fronto-temporal left-lateralized "core" language network, which is selectively recruited by linguistic processing. Is the language network distinct and dissociated from both the MD network and the DMN, or is it synchronized and integrated with one or both of them? Recent work has provided evidence for a dissociation between the language network and the MD network. However, the relationship between the language network and the DMN is less clear, with some evidence for coordinated activity patterns and similar response profiles, perhaps due to the role of both in semantic processing. Here we use a novel fMRI approach to examine the relationship among the three networks: we measure the strength of activations in different language, MD, and DMN regions to functional contrasts typically used to identify each network, and then test which regions co-vary in their contrast effect sizes across 60 individuals. We find that effect sizes correlate strongly within each network (e.g., one language region and another language region, or one DMN region and another DMN region), but show little or no correlation for region pairs across networks (e.g., a language region and a DMN region). Thus, using our novel method, we replicate the language/MD network dissociation discovered previously with other approaches, and also show that the language network is robustly dissociated from the DMN, overall suggesting that these three networks contribute to high-level cognition in different ways and, perhaps, support distinct computations. Inter-individual differences in effect sizes therefore do not simply reflect general differences in vascularization or attention, but exhibit sensitivity to the functional architecture of the brain. The strength of activation in each network can thus be probed separately in studies that attempt to link neural variability to behavioral or genetic variability.

Real-time monitoring prefrontal activities during online video game playing by functional near-infrared spectroscopy

A growing body of literature has suggested that video game playing can induce functional and structural plasticity of the brain. The underlying mechanisms, however, remain poorly understood. In this study, functional near-infrared spectroscopy (fNIRS) was used to record prefrontal activities in 24 experienced game players when they played a massively multiplayer online battle arena video game, League of Legends (LOL), under naturalistic conditions. It was observed that game onset was associated with significant activations in the ventrolateral prefrontal cortex (VLPFC) and concomitant deactivations in the dorsolateral prefrontal cortex (DLPFC) and frontal pole area (FPA). Game events, such as slaying an enemy and being slain by an enemy evoked region-specific time-locked hemodynamic/oxygenation responses in the prefrontal cortex (PFC). It was proposed that the VLPFC activities during LOL playing are likely responses to visuo-motor task load of the game, while the DLPFC/FPA activities may be involved in the constant shifts of attentional states and allocation of cognitive resources required by game playing. The present study demonstrated that it is feasible to use fNIRS to monitor real-time prefrontal activity during online video game playing.

Task-Evoked Negative BOLD Response in the Default Mode Network Does Not Alter Its Functional Connectivity

While functional connectivity networks are often extracted from resting-state fMRI scans, they have been shown to be active during task performance as well. However, the effect of an in-scanner task on functional connectivity networks is not completely understood. While there is evidence that task-evoked positive BOLD response can alter functional connectivity networks, particularly in the primary sensorimotor cortices, the effect of task-evoked negative BOLD response on the functional connectivity of the Default mode network (DMN) is somewhat ambiguous. In this study, we aim to investigate whether task performance, which is associated with negative BOLD response in the DMN regions, alters the time-course of functional connectivity in the same regions obtained by independent component analysis (ICA). ICA has been used to effectively extract functional connectivity networks during task performance and resting-state. We first demonstrate that performing a simple visual-motor task alters the temporal time-course of the network extracted from the primary visual cortex. Then we show that despite detecting a robust task-evoked negative BOLD response in the DMN regions, a simple visual-motor task does not alter the functional connectivity of the DMN regions. Our findings suggest that different mechanisms may underlie the relationship between task-related activation/deactivation networks and the overlapping functional connectivity networks in the human large-scale brain networks.

Semantically defined subdomains of functional neuroimaging literature and their corresponding brain regions

The functional neuroimaging literature has become increasingly complex and thus difficult to navigate. This complexity arises from the rate at which new studies are published and from the terminology that varies widely from study-to-study and even more so from discipline-to-discipline. One way to investigate and manage this problem is to build a "semantic space" that maps the different vocabulary used in functional neuroimaging literature. Such a semantic space will also help identify the primary research domains of neuroimaging and their most commonly reported brain regions. In this work, we analyzed the multivariate semantic structure of abstracts in Neurosynth and found that there are six primary domains of the functional neuroimaging literature, each with their own preferred reported brain regions. Our analyses also highlight possible semantic sources of reported brain regions within and across domains because some research topics (e.g., memory disorders, substance use disorder) use heterogeneous terminology. Furthermore, we highlight the growth and decline of the primary domains over time. Finally, we note that our techniques and results form the basis of a "recommendation engine" that could help readers better navigate the neuroimaging literature.

On testing for spatial correspondence between maps of human brain structure and function

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data.

Frontoparietal Functional Connectivity in the Common Marmoset

In contrast to the well established macaque monkey, little is known about functional connectivity patterns of common marmoset monkey (Callithrix jacchus) that is poised to become the leading transgenic primate model. Here, we used resting-state ultra-high-field fMRI data collected from anesthetized marmosets and macaques along with awake human subjects, to examine and compare the brain's functional organization, with emphasis on the saccade system. Exploratory independent component analysis revealed eight resting-state networks in marmosets that greatly overlapped with corresponding macaque and human networks including a distributed frontoparietal network. Seed-region analyses of the superior colliculus (SC) showed homolog areas in macaques and marmosets. The marmoset SC displayed the strongest frontal functional connectivity with area 8aD at the border to area 6DR. Functional connectivity of this frontal region revealed a similar functional connectivity pattern as the frontal eye fields in macaques and humans. Furthermore, areas 8aD, 8aV, PG,TPO, TE2, and TE3 were identified as major hubs based on region-wise evaluation of betweeness centrality, suggesting that these cortical regions make up the functional core of the marmoset brain. The results support an evolutionarily preserved frontoparietal system and provide a starting point for invasive neurophysiological studies in the marmoset saccade and visual systems.

Whole Brain Functional Connectivity Pattern Homogeneity Mapping

Mounting studies have demonstrated that brain functions are determined by its external functional connectivity patterns. However, how to characterize the voxel-wise similarity of whole brain functional connectivity pattern is still largely unknown. In this study, we introduced a new method called functional connectivity homogeneity (FcHo) to delineate the voxel-wise similarity of whole brain functional connectivity patterns. FcHo was defined by measuring the whole brain functional connectivity patterns similarity of a given voxel with its nearest 26 neighbors using Kendall's coefficient concordance (KCC). The robustness of this method was tested in four independent datasets selected from a large repository of MRI. Furthermore, FcHo mapping results were further validated using the nearest 18 and six neighbors and intra-subject reproducibility with each subject scanned two times. We also compared FcHo distribution patterns with local regional homogeneity (ReHo) to identify the similarity and differences of the two methods. Finally, FcHo method was used to identify the differences of whole brain functional connectivity patterns between professional Chinese chess players and novices to test its application. FcHo mapping consistently revealed that the high FcHo was mainly distributed in association cortex including parietal lobe, frontal lobe, occipital lobe and default mode network (DMN) related areas, whereas the low FcHo was mainly found in unimodal cortex including primary visual cortex, sensorimotor cortex, paracentral lobule and supplementary motor area. These results were further supported by analyses of the nearest 18 and six neighbors and intra-subject similarity. Moreover, FcHo showed both similar and different whole brain distribution patterns compared to ReHo. Finally, we demonstrated that FcHo can effectively identify the whole brain functional connectivity pattern differences between professional Chinese chess players and novices. Our findings indicated that FcHo is a reliable method to delineate the whole brain functional connectivity pattern similarity and may provide a new way to study the functional organization and to reveal neuropathological basis for brain disorders.

Mild cognitive impairment disrupts attention network connectivity in Parkinson's disease: A combined multimodal MRI and meta-analytical study

Mild cognitive impairment (MCI) affects approximately one-third of non-demented Parkinson's Disease (PD) patients. We aimed at investigating the neural correlates of MCI in PD combining multimodal magnetic resonance imaging (MRI) with large-scale data from the literature. We analyzed 31 PD patients and 30 matched controls. The standard neuropsychological assessment of PD-MCI covered memory, attention, executive functions, language and visuospatial abilities. Following validated criteria, 16 patients were classified as showing MCI. Whole-brain functional connectivity and structural volume changes were assessed, respectively, by means of eigenvector centrality (EC) and voxel-based morphometry. To address the involvement of specific functional brain networks, we validated our results by building a meta-analytic co-activation map (MACM) based on the previous literature and then testing its overlap with the parcellation of functional networks derived from 1000 healthy controls. The EC comparison between PD with normal cognition and controls showed a selective decline in interconnectedness in the bilateral lentiform nuclei. Differently, comparing PD with MCI and controls revealed additional changes in non-motor areas. Directly comparing PD with and without MCI, we found a reduced interconnectedness in the bilateral superior parietal lobules and precuneus. No differences in brain volume were detected comparing these patient groups. The MACM and overlap analyses showed that the observed connectivity changes were localized in the hubs of the dorsal attention network. Notably, this aligned with the predominant attention deficit observed in our sample. Overall, functional impairment in the dorsal attention network seems to be the hallmark of MCI due to PD, thus extending previous findings of brain connectivity disruption in non-motor networks.

Gamma-hydroxybutyrate increases brain resting-state functional connectivity of the salience network and dorsal nexus in humans

According to the triple network hypothesis the brain is equipped with three core neurocognitive networks: the default mode (DMN), the salience (SN), and the central executive (CEN) network. Moreover, the so called dorsal nexus, has met growing interest as it is a hub region connecting these three networks. Assessment of resting-state functional connectivity (rsFC) of these networks enables the elucidation of drug-induced brain alterations. Gamma-hydroxybutyrate (GHB) is a GHB/GABA-B receptor agonist that induces a paradoxical state of mixed stimulation and sedation at moderate doses, which makes it a valuable tool to investigate neural signatures of subjective drug effects. Employing a placebo-controlled, double-blind, randomized, cross-over design, we assessed the effects of GHB (35 mg/kg p. o.) in 19 healthy male subjects on DMN-, SN-, CEN-, and dorsal nexus-rsFC measured by functional magnet resonance imaging and applying independent component as well as seed-based analyses, while subjective drug effects were investigated using visual analog scales (VAS). Subjectively, GHB increased VAS ratings of a general drug effect, stimulation, and sedation. Intrinsic DMN-, and CEN-rsFC remained largely unchanged under GHB, but the drug increased SN-DMN-rsFC and SN-dorsal nexus-rsFC, while dorsal nexus-rsFC was reciprocally increased to both the SN (right anterior insula) and to the CEN (right middle frontal gyrus). Increased sedation significantly predicted the observed SN-dorsal nexus-rsFC. In conclusion, GHB generates a unique stimulant/sedative subjective state that is paralleled by a complex pattern of increased functional connectivity encompassing all three core neurocognitive networks of the brain, while increased SN-dorsal nexus-rsFC was demonstrated to be a potential signature of the sedative component of the drug effect.

Co-activation patterns in resting-state fMRI signals

The brain is a complex system that integrates and processes information across multiple time scales by dynamically coordinating activities over brain regions and circuits. Correlations in resting-state functional magnetic resonance imaging (rsfMRI) signals have been widely used to infer functional connectivity of the brain, providing a metric of functional associations that reflects a temporal average over an entire scan (typically several minutes or longer). Not until recently was the study of dynamic brain interactions at much shorter time scales (seconds to minutes) considered for inference of functional connectivity. One method proposed for this objective seeks to identify and extract recurring co-activation patterns (CAPs) that represent instantaneous brain configurations at single time points. Here, we review the development and recent advancement of CAP methodology and other closely related approaches, as well as their applications and associated findings. We also discuss the potential neural origins and behavioral relevance of CAPs, along with methodological issues and future research directions in the analysis of fMRI co-activation patterns.

Intrinsic optical signal imaging of the blood volume changes is sufficient for mapping the resting state functional connectivity in the rodent cortex

OBJECTIVE

Resting state functional connectivity (RSFC) allows the study of functional organization in normal and diseased brain by measuring the spontaneous brain activity generated under resting conditions. Intrinsic optical signal imaging (IOSI) based on multiple illumination wavelengths has been used successfully to compute RSFC maps in animal studies. The IOSI setup complexity would be greatly reduced if only a single wavelength can be used to obtain comparable RSFC maps.

APPROACH

We used anesthetized mice and performed various comparisons between the RSFC maps based on single wavelength as well as oxy-, deoxy- and total hemoglobin concentration changes.

MAIN RESULTS

The RSFC maps based on IOSI at a single wavelength selected for sensitivity to the blood volume changes are quantitatively comparable to the RSFC maps based on oxy- and total hemoglobin concentration changes obtained by the more complex IOSI setups. Moreover, RSFC maps do not require CCD cameras with very high frame acquisition rates, since our results demonstrate that they can be computed from the data obtained at frame rates as low as 5 Hz.

SIGNIFICANCE

Our results will have general utility for guiding future RSFC studies based on IOSI and making decisions about the IOSI system designs.

How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study

•In chronic pain, gray matter (GM) alterations are not distributed randomly across the brain.•The pattern of co-alterations resembles that of brain connectivity.•The alterations' distribution partly rely on the pathways of functional connectivity.•This method allows us to identify tendencies in the distribution of GM co-alteration related to chronic pain.

Altered intrinsic and extrinsic connectivity in schizophrenia

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

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A first use of hierarchical modeling of effective connectivity to characterize large-scale networks in schizophrenia.

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Intrinsic and extrinsic effective connectivity involving prefrontal regions were abnormal in schizophrenia.

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Diagnostic connections could predict the severity of clinical symptoms and cognition in schizophrenia.

Cognitive Characterization of Schizophrenia Risk Variants Involved in Synaptic Transmission: Evidence of CACNA1C's Role in Working Memory

With >100 common variants associated with schizophrenia risk, establishing their biological significance is a priority. We sought to establish cognitive effects of risk variants at loci implicated in synaptic transmission by (1) identifying GWAS schizophrenia variants whose associated gene function is related to synaptic transmission, and (2) testing for association between these and measures of neurocognitive function. We selected variants, reported in the largest GWAS to date, associated with genes involved in synaptic transmission. Associations between genotype and cognitive test score were analyzed in a discovery sample (988 Irish participants, including 798 with psychosis), and replication samples (528 UK patients with schizophrenia/schizoaffective disorder; 921 German participants including 362 patients with schizophrenia). Three loci showed significant associations with neuropsychological performance in the discovery samples. This included an association between the rs2007044 (risk allele G) within CACNA1C and poorer working memory performance (increased errors B (95% CI)=0.635-4.535, p=0.012), an effect driven mainly by the psychosis groups. In an fMRI analysis of working memory performance (n=84 healthy participants, a subset of the discovery sample), we further found evidence that the same CACNA1C allele was associated with decreased functional connectivity between the right dorsolateral prefrontal cortex and right superior occipital gyrus/cuneus and anterior cingulate cortex. In conclusion, these data provide evidence to suggest that the CACNA1C risk variant rs2007044 is associated with poorer memory function that may result from risk carriers' difficulty with top-down initiated responses caused by dysconnectivity between the right DLPFC and several cortical regions.

On the role of the corpus callosum in interhemispheric functional connectivity in humans

The relation between structural and functional connectivity has profound implications for our understanding of cerebral physiology and cognitive neuroscience. Yet, this relation remains incompletely understood. Cases in which the corpus callosum is sectioned for medical reasons provide a unique opportunity to study this question. We report functional connectivity assessed before and after surgical section of the corpus callosum, including multiyear follow-up in a limited subsample. Our results demonstrate a causal role for the corpus callosum in maintaining functional connectivity between the hemispheres. Additionally, comparison of results obtained in complete vs. partial callosotomy demonstrate that polysynaptic connections also play a role in maintaining interhemispheric functional connectivity.

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity.

Posterior dopamine D2/3 receptors and brain network functional connectivity

Recent studies suggest that dopaminergic tone influences resting state activity in multiple brain networks. Although dopamine receptors and transporters have been identified in the posteromedial and parietal cortices, which are linked to functional networks such as the default mode network (DMN), the relationship between dopamine receptor distribution in these posterior regions and resting-state connectivity has yet to be explored. Here, we used a multi-modal neuroimaging strategy, combining resting-state functional magnetic resonance imaging (rsfMRI) and [18 F]-fallypride high-resolution positron emission tomography (PET), to examine the association between within-network functional connectivity and the dopamine D2/3 receptor distribution in the posterior portion of the brain in 13 healthy adults. Our results indicate that the posterior distribution of D2/3 receptors coincides primarily with the posterior portion of the DMN. Furthermore, in the posterior portion of the brain, the level of [18 F]-fallypride binding in the posteromedial cortex correlated positively with the functional connectivity strength of the DMN and sensorimotor network, and negatively with the functional connectivity strength of the dorsal attention network, the salience network, and a network that included the anterior part of the temporo-parietal junction. On the basis of these findings, we propose that posterior brain dopamine influences the configuration of the posterior DMN and several other functional brain networks. The posterior distribution of D2/3 receptors binding (hot colour spectrum) coincides with the functional connectivity of the posterior portion of the default mode network (green colour spectrum). The mean BP_ND in a posteromedial cortex and the mean ICA-Z score in the precuneus showed significant positive correlation.

Task-based dynamic functional connectivity: Recent findings and open questions

The temporal evolution of functional connectivity (FC) within the confines of individual scans is nowadays often explored with functional neuroimaging. This is particularly true for resting-state; yet, FC-dynamics have also been investigated as subjects engage on numerous tasks. It is these research efforts that constitute the core of this survey. First, empirical observations on how FC differs between task and rest-independent of temporal scale-are reviewed, as they underscore how, despite overall preservation of network topography, the brain's FC does reconfigure in systematic ways to accommodate task demands. Next, reports on the relationships between instantaneous FC and perception/performance in subsequent trials are discussed. Similarly, research where different aspects of task-concurrent FC-dynamics are explored or utilized to predict ongoing mental states are also examined. The manuscript finishes with an incomplete list of challenges that hopefully fuels future work in this vibrant area of neuroscientific research. Overall, this review concludes that task-concurrent FC-dynamics, when properly characterized, are relevant to behavior, and that their translational value holds considerable promise.

Large-Scale Meta-Analysis of Human Medial Frontal Cortex Reveals Tripartite Functional Organization

The functional organization of human medial frontal cortex (MFC) is a subject of intense study. Using fMRI, the MFC has been associated with diverse psychological processes, including motor function, cognitive control, affect, and social cognition. However, there have been few large-scale efforts to comprehensively map specific psychological functions to subregions of medial frontal anatomy. Here we applied a meta-analytic data-driven approach to nearly 10,000 fMRI studies to identify putatively separable regions of MFC and determine which psychological states preferentially recruit their activation. We identified regions at several spatial scales on the basis of meta-analytic coactivation, revealing three broad functional zones along a rostrocaudal axis composed of 2-4 smaller subregions each. Multivariate classification analyses aimed at identifying the psychological functions most strongly predictive of activity in each region revealed a tripartite division within MFC, with each zone displaying a relatively distinct functional signature. The posterior zone was associated preferentially with motor function, the middle zone with cognitive control, pain, and affect, and the anterior with reward, social processing, and episodic memory. Within each zone, the more fine-grained subregions showed distinct, but subtler, variations in psychological function. These results provide hypotheses about the functional organization of medial prefrontal cortex that can be tested explicitly in future studies.

SIGNIFICANCE STATEMENT

Activation of medial frontal cortex in fMRI studies is associated with a wide range of psychological states ranging from cognitive control to pain. However, this high rate of activation makes it challenging to determine how these various processes are topologically organized across medial frontal anatomy. We conducted a meta-analysis across nearly 10,000 studies to comprehensively map psychological states to discrete subregions in medial frontal cortex using relatively unbiased data-driven methods. This approach revealed three distinct zones that differed substantially in function, each of which were further subdivided into 2-4 smaller subregions that showed additional functional variation. Each individual region was recruited by multiple psychological states, suggesting subregions of medial frontal cortex are functionally heterogeneous.

Data-Driven Extraction of a Nested Model of Human Brain Function

Decades of cognitive neuroscience research have revealed two basic facts regarding task-driven brain activation patterns. First, distinct patterns of activation occur in response to different task demands. Second, a superordinate, dichotomous pattern of activation/deactivation, is common across a variety of task demands. We explore the possibility that a hierarchical model incorporates these two observed brain activation phenomena into a unifying framework. We apply a latent variable approach, exploratory bifactor analysis, to a large set of human (both sexes) brain activation maps (n = 108) encompassing cognition, perception, action, and emotion behavioral domains, to determine the potential existence of a nested structure of factors that underlie a variety of commonly observed activation patterns. We find that a general factor, associated with a superordinate brain activation/deactivation pattern, explained the majority of the variance (52.37%) in brain activation patterns. The bifactor analysis also revealed several subfactors that explained an additional 31.02% of variance in brain activation patterns, associated with different manifestations of the superordinate brain activation/deactivation pattern, each emphasizing different contexts in which the task demands occurred. Importantly, this nested factor structure provided better overall fit to the data compared with a non-nested factor structure model. These results point to a domain-general psychological process, representing a "focused awareness" process or "attentional episode" that is variously manifested according to the sensory modality of the stimulus and degree of cognitive processing. This novel model provides the basis for constructing a biologically informed, data-driven taxonomy of psychological processes.SIGNIFICANCE STATEMENT A crucial step in identifying how the brain supports various psychological processes is a well-defined categorization or taxonomy of psychological processes and their interrelationships. We hypothesized that a nested structure of cognitive function, in terms of a canonical domain-general cognitive process, and various subfactors representing different manifestations of the canonical process, is a fundamental organization of human cognition, and we tested this hypothesis using fMRI task-activation patterns. Using a data-driven latent-variable approach, we demonstrate that a nested factor structure underlies a large sample of brain activation patterns across a variety of task domains.

Improved 7 Tesla resting-state fMRI connectivity measurements by cluster-based modeling of respiratory volume and heart rate effects

Several strategies have been proposed to model and remove physiological noise from resting-state fMRI (rs-fMRI) data, particularly at ultrahigh fields (7 T), including contributions from respiratory volume (RV) and heart rate (HR) signal fluctuations. Recent studies suggest that these contributions are highly variable across subjects and that physiological noise correction may thus benefit from optimization at the subject or even voxel level. Here, we systematically investigated the impact of the degree of spatial specificity (group, subject, newly proposed cluster, and voxel levels) on the optimization of RV and HR models. For each degree of spatial specificity, we measured the fMRI signal variance explained (VE) by each model, as well as the functional connectivity underlying three well-known resting-state networks (RSNs) obtained from the fMRI data after removal of RV+HR contributions. Whole-brain, high-resolution rs-fMRI data were acquired from twelve healthy volunteers at 7 T, while simultaneously recording their cardiac and respiratory signals. Although VE increased with spatial specificity up to the voxel level, the accuracy of functional connectivity measurements improved only up to the cluster level, and subsequently decreased at the voxel level. This suggests that voxelwise modeling over-fits to local fluctuations with no physiological meaning. In conclusion, our results indicate that 7 T rs-fMRI connectivity measurements improve if a cluster-based physiological noise correction approach is employed in order to take into account the individual spatial variability in the HR and RV contributions.

Continuous positive airway pressure therapy in obstuctive sleep apnea: benefits and alternatives

INTRODUCTION

Obstructive sleep apnea (OSA) is a highly prevalent condition affecting persons of all age with an increasing public health burden. It is implicated in cardiovascular disease, metabolic syndrome, neurocognitive impairment, reductions in quality of life, and increased motor vehicle accidents. The goals of OSA treatment are to improve sleep and daytime symptoms, and minimize cardiovascular risks.Areas covered: Continuous positive airway pressure (CPAP) is considered the gold standard therapy that delivers pressurized air into the upper airway to relieve obstruction during sleep. Although CPAP is an effective modality of treatment for OSA, adherence to therapy is highly variable. This article highlights the benefits of CPAP therapy, along with alternative treatment options including oral appliance, implantable and wearable devices, and surgery. Expert commentary: CPAP therapy is the gold standard treatment option and should continue to be offered to those who suffer from OSA. Alternative options are available for those who are unable to adhere to CPAP or choose an alternative treatment modality. The most interesting advances have been incorporating orthodontic procedures in conjunction with myofunctional therapy in prepubertal children, raising the possibility of OSA prevention by initiating treatment early in life.

Task-linked Diurnal Brain Network Reorganization in Older Adults: A Graph Theoretical Approach

Testing older adults in the morning generally improves behavioral performance relative to afternoon testing. Morning testing is also associated with brain activity similar to that of young adults. Here, we used graph theory to explore how time of day (TOD) affects the organization of brain networks in older adults across rest and task states. We used nodes from the automated anatomical labeling atlas to construct participant-specific correlation matrices of fMRI data obtained during 1-back tasks with interference and rest. We computed pairwise group differences for key graph metrics, including small-worldness and modularity. We found that older adults tested in the morning and young adults did not differ on any graph metric. Both of these groups differed from older adults tested in the afternoon during the tasks—but not rest. Specifically, the latter group had lower modularity and small-worldness (indices of more efficient network organization). Across all groups, higher modularity and small-worldness strongly correlated with reduced distractibility on an implicit priming task. Increasingly, TOD is seen as important for interpreting and reproducing neuroimaging results. Our study emphasizes how TOD affects brain network organization and executive control in older adults.

Corpus callosal atrophy and associations with cognitive impairment in Parkinson disease

OBJECTIVE

To investigate atrophy of the corpus callosum on MRI in Parkinson disease (PD) and its relationship to cognitive impairment.

METHODS

One hundred patients with PD and 24 healthy control participants underwent clinical and neuropsychological evaluations and structural MRI brain scans. Participants with PD were classified as cognitively normal (PD-NC; n = 28), having mild cognitive impairment (PD-MCI; n = 47), or having dementia (PDD; n = 25) by Movement Disorder Society criteria. Cognitive domain (attention/working memory, executive function, memory, language, visuospatial function) z scores were calculated. With the use of FreeSurfer image processing, volumes for total corpus callosum and its subsections (anterior, midanterior, central, midposterior, posterior) were computed and normalized by total intracranial volume. Callosal volumes were compared between participants with PD and controls and among PD cognitive groups, covarying for age, sex, and PD duration and with multiple comparison corrections. Regression analyses were performed to evaluate relationships between callosal volumes and performance in cognitive domains.

RESULTS

Participants with PD had reduced corpus callosum volumes in midanterior and central regions compared to healthy controls. Participants with PDD demonstrated decreased callosal volumes involving multiple subsections spanning anterior to posterior compared to participants with PD-MCI and PD-NC. Regional callosal atrophy predicted cognitive domain performance such that central volumes were associated with the attention/working memory domain; midposterior volumes with executive function, language, and memory domains; and posterior volumes with memory and visuospatial domains.

CONCLUSIONS

Notable volume loss occurs in the corpus callosum in PD, with specific neuroanatomic distributions in PDD and relationships of regional atrophy to different cognitive domains. Callosal volume loss may contribute to clinical manifestations of PD cognitive impairment.

Interhemispheric functional connectivity in anorexia and bulimia nervosa

The functional interplay between hemispheres is fundamental for behavioral, cognitive, and emotional control. Anorexia nervosa (AN) and bulimia nervosa (BN) have been largely studied with brain magnetic resonance imaging (MRI) in relation to the functional mechanisms of high-level processing, but not in terms of possible inter-hemispheric functional connectivity anomalies. Using resting-state functional MRI (fMRI), voxel-mirrored homotopic connectivity (VMHC) and regional inter-hemispheric spectral coherence (IHSC) were studied in 15 AN and 13 BN patients and 16 healthy controls (HC). Using T1-weighted and diffusion tensor imaging MRI scans, regional VMHC values were correlated with the left-right asymmetry of corresponding homotopic gray matter volumes and with the white matter callosal fractional anisotropy (FA). Compared to HC, AN patients exhibited reduced VMHC in cerebellum, insula, and precuneus, while BN patients showed reduced VMHC in dorso-lateral prefrontal and orbito-frontal cortices. The regional IHSC analysis highlighted that the inter-hemispheric functional connectivity was higher in the 'Slow-5' band in all regions except the insula. No group differences in left-right structural asymmetries and in VMHC vs. callosal FA correlations were significant in the comparisons between cohorts. These anomalies, not explained by structural changes, indicate that AN and BN, at least in their acute phase, are associated with a loss of inter-hemispheric connectivity in regions implicated in self-referential, cognitive control and reward processing. These findings may thus gather novel functional markers to explore aberrant features of these eating disorders.