Spatially Distributed Effects of Mental Exhaustion on Resting-State FMRI Networks

Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.     

Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder

Conduct disorder (CD) is characterized by a persistent pattern of antisocial behavior and aggression in childhood and adolescence. Previous task-based and resting-state functional magnetic resonance imaging (fMRI) studies have revealed widespread brain regional abnormalities in adolescents with CD. However, whether the resting-state networks (RSNs) are altered in adolescents with CD remains unknown. In this study, resting-state fMRI data were first acquired from eighteen male adolescents with pure CD and eighteen age- and gender-matched typically developing (TD) individuals. Independent component analysis (ICA) was implemented to extract nine representative RSNs, and the generated RSNs were then compared to show the differences between the CD and TD groups. Interestingly, it was observed from the brain mapping results that compared with the TD group, the CD group manifested decreased functional connectivity in four representative RSNs: the anterior default mode network (left middle frontal gyrus), which is considered to be correlated with impaired social cognition, the somatosensory network (bilateral supplementary motor area and right postcentral gyrus), the lateral visual network (left superior occipital gyrus), and the medial visual network (right fusiform, left lingual gyrus and right calcarine), which are expected to be relevant to the perceptual systems responsible for perceptual dysfunction in male adolescents with CD. Importantly, the novel findings suggested that male adolescents with pure CD were identified to have dysfunctions in both low-level perceptual networks (the somatosensory network and visual network) and a high-order cognitive network (the default mode network). Revealing the changes in the functional connectivity of these RSNs enhances our understanding of the neural mechanisms underlying the modulation of emotion and social cognition and the regulation of perception in adolescents with CD.     

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

Background

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.

Methodology/Principal Findings

We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.

Conclusions/Significance

These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.     

White Matter Hyperintensities among Older Adults Are Associated with Futile Increase in Frontal Activation and Functional Connectivity during Spatial Search

The mechanisms by which aging and other processes can affect the structure and function of brain networks are important to understanding normal age-related cognitive decline. Advancing age is known to be associated with various disease processes, including clinically asymptomatic vascular and inflammation processes that contribute to white matter structural alteration and potential injury. The effects of these processes on the function of distributed cognitive networks, however, are poorly understood. We hypothesized that the extent of magnetic resonance imaging white matter hyperintensities would be associated with visual attentional control in healthy aging, measured using a functional magnetic resonance imaging search task. We assessed cognitively healthy older adults with search tasks indexing processing speed and attentional control. Expanding upon previous research, older adults demonstrate activation across a frontal-parietal attentional control network. Further, greater white matter hyperintensity volume was associated with increased activation of a frontal network node independent of chronological age. Also consistent with previous research, greater white matter hyperintensity volume was associated with anatomically specific reductions in functional magnetic resonance imaging functional connectivity during search among attentional control regions. White matter hyperintensities may lead to subtle attentional network dysfunction, potentially through impaired frontal-parietal and frontal interhemispheric connectivity, suggesting that clinically silent white matter biomarkers of vascular and inflammatory injury can contribute to differences in search performance and brain function in aging, and likely contribute to advanced age-related impairments in cognitive control.     

Investigations into resting-state connectivity using independent component analysis

Inferring resting-state connectivity patterns from functional magnetic resonance imaging (fMRI) data is a challenging task for any analytical technique. In this paper, we review a probabilistic independent component analysis (PICA) approach, optimized for the analysis of fMRI data, and discuss the role which this exploratory technique can take in scientific investigations into the structure of these effects. We apply PICA to fMRI data acquired at rest, in order to characterize the spatio-temporal structure of such data, and demonstrate that this is an effective and robust tool for the identification of low-frequency resting-state patterns from data acquired at various different spatial and temporal resolutions. We show that these networks exhibit high spatial consistency across subjects and closely resemble discrete cortical functional networks such as visual cortical areas or sensory-motor cortex.     

Resting-State fMRI Functional Connectivity Is Associated with Sleepiness,Imagery, and Discontinuity of Mind

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies.     

Comparing structural and functional graph theory features in the human brain using multimodal MRI

Recent advances in magnetic resonance imaging (MRI) are allowing neuroscientists to gain critical insights into the neural networks mediating a variety of cognitive processes. This work investigates structural and functional connectivity in the human brain under different experimental conditions through multimodal MRI acquisitions. To define the nodes of a full-brain network, a set of regions was identified from resting-state functional MRI (fMRI) data using spatial independent component analysis (sICA) and a hierarchical clustering technique. Diffusion-weighted imaging (DWI) data were acquired from the same subjects and a probabilistic fiber tracking method was used to estimate the structure of this network. Using features originating from graph theory, such as small-world properties and network efficiency, we characterized the structural and functional connectivities of the full-brain network and we compared them quantitatively. We showed that structural and functional networks shared some properties in terms of topology as measured by the distribution of the node degrees, hence supporting the existence of an underlying anatomical substrate for functional networks.     

Modulatory Interactions of Resting-State Brain Functional Connectivity

The functional brain connectivity studies are generally based on the synchronization of the resting-state functional magnetic resonance imaging (fMRI) signals. Functional connectivity measures usually assume a stable relationship over time; however, accumulating studies have reported time-varying properties of strength and spatial distribution of functional connectivity. The present study explored the modulation of functional connectivity between two regions by a third region using the physiophysiological interaction (PPI) technique. We first identified eight brain networks and two regions of interest (ROIs) representing each of the networks using a spatial independent component analysis. A voxel-wise analysis was conducted to identify regions that showed modulatory interactions (PPI) with the two ROIs of each network. Mostly, positive modulatory interactions were observed within regions involved in the same system. For example, the two regions of the dorsal attention network revealed modulatory interactions with the regions related to attention, while the two regions of the extrastriate network revealed modulatory interactions with the regions in the visual cortex. In contrast, the two regions of the default mode network (DMN) revealed negative modulatory interactions with the regions in the executive network, and vice versa, suggesting that the activities of one network may be associated with smaller within network connectivity of the competing network. These results validate the use of PPI analysis to study modulation of resting-state functional connectivity by a third region. The modulatory effects may provide a better understanding of complex brain functions.     

Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI

A number of previous studies have examined music-related plasticity in terms of multi-sensory and motor integration but little is known about the functional and effective connectivity patterns of spontaneous intrinsic activity in these systems during the resting state in musicians. Using functional connectivity and Granger causal analysis, functional and effective connectivity among the motor and multi-sensory (visual, auditory and somatosensory) cortices were evaluated using resting-state functional magnetic resonance imaging (fMRI) in musicians and non-musicians. The results revealed that functional connectivity was significantly increased in the motor and multi-sensory cortices of musicians. Moreover, the Granger causality results demonstrated a significant increase outflow-inflow degree in the auditory cortex with the strongest causal outflow pattern of effective connectivity being found in musicians. These resting state fMRI findings indicate enhanced functional integration among the lower-level perceptual and motor networks in musicians, and may reflect functional consolidation (plasticity) resulting from long-term musical training, involving both multi-sensory and motor functional integration.     

fMRI Resting Slow Fluctuations Correlate with the Activity of Fast Cortico-Cortical Physiological Connections

Recording of slow spontaneous fluctuations at rest using functional magnetic resonance imaging (fMRI) allows distinct long-range cortical networks to be identified. The neuronal basis of connectivity as assessed by resting-state fMRI still needs to be fully clarified, considering that these signals are an indirect measure of neuronal activity, reflecting slow local variations in de-oxyhaemoglobin concentration. Here, we combined fMRI with multifocal transcranial magnetic stimulation (TMS), a technique that allows the investigation of the causal neurophysiological interactions occurring in specific cortico-cortical connections. We investigated whether the physiological properties of parieto-frontal circuits mapped with short-latency multifocal TMS at rest may have some relationship with the resting-state fMRI measures of specific resting-state functional networks (RSNs). Results showed that the activity of fast cortico-cortical physiological interactions occurring in the millisecond range correlated selectively with the coupling of fMRI slow oscillations within the same cortical areas that form part of the dorsal attention network, i.e., the attention system believed to be involved in reorientation of attention. We conclude that resting-state fMRI ongoing slow fluctuations likely reflect the interaction of underlying physiological cortico-cortical connections.     

Neural correlates of the attentional blink

Attending to a visual event can lead to functional blindness for other events in the visual field. This limit in our attentional capacities is exemplified by the attentional blink (AB), which refers to the transient but severe impairment in perceiving the second of two temporally neighboring targets. Using functional magnetic resonance imaging (fMRI), we observed predominantly right intraparietal and frontal cortex activations associated with the AB. We further demonstrate that an AB can be elicited by both temporal and spatial distractor interference on an attended target and that both of these interference mechanisms activate the same neural circuit. These results suggest that a (right) parietofrontal network previously implicated in attentional control and enhancement is also a locus of capacity-limited processing of visual information.     

Spatio-Temporal Correlation Tensors Reveal Functional Structure in Human Brain

Resting state functional magnetic resonance imaging (fMRI) has been commonly used to measure functional connectivity between cortical regions, while diffusion tensor imaging (DTI) can be used to characterize structural connectivity of white matter tracts. In principle combining resting state fMRI and DTI data could allow characterization of structure-function relations of distributed neural networks. However, due to differences in the biophysical origins of their signals and in the tissues to which they apply, there has been no direct integration of these techniques to date. We demonstrate that MRI signal variations and power spectra in a resting state are largely comparable between gray matter and white matter, that there are temporal correlations of fMRI signals that persist over long distances within distinct white matter structures, and that neighboring intervoxel correlations of low frequency resting state signals showed distinct anisotropy in many regions. These observations suggest that MRI signal variations from within white matter in a resting state may convey similar information as their corresponding fluctuations of MRI signals in gray matter. We thus derive a local spatio-temporal correlation tensor which captures directional variations of resting-state correlations and which reveals distinct structures in both white and gray matter. This novel concept is illustrated with in vivo experiments in a resting state, which demonstrate the potential of the technique for mapping the functional structure of neural networks and for direct integration of structure-function relations in the human brain.     

Topological fractionation of resting-state networks

Exploring topological properties of human brain network has become an exciting topic in neuroscience research. Large-scale structural and functional brain networks both exhibit a small-world topology, which is evidence for global and local parallel information processing. Meanwhile, resting state networks (RSNs) underlying specific biological functions have provided insights into how intrinsic functional architecture influences cognitive and perceptual information processing. However, topological properties of single RSNs remain poorly understood. Here, we have two hypotheses: i) each RSN also has optimized small-world architecture; ii) topological properties of RSNs related to perceptual and higher cognitive processes are different. To test these hypotheses, we investigated the topological properties of the default-mode, dorsal attention, central-executive, somato-motor, visual and auditory networks derived from resting-state functional magnetic resonance imaging (fMRI). We found small-world topology in each RSN. Furthermore, small-world properties of cognitive networks were higher than those of perceptual networks. Our findings are the first to demonstrate a topological fractionation between perceptual and higher cognitive networks. Our approach may be useful for clinical research, especially for diseases that show selective abnormal connectivity in specific brain networks.     

Interactions between the neural correlates of dispositional internally directed thought and visual imagery

Cognition is not always directed to the events in the here and now and we often self-generate thoughts and images in imagination. Important aspects of these self-generated experiences are associated with various dispositional traits. In this study, we explored whether these psychological associations relate to a common underlying neurocognitive mechanism. We acquired resting state functional magnetic resonance imaging data from a large cohort of participants and asked them to retrospectively report their experience during the scan. Participants also completed questionnaires reflecting a range of dispositional traits. We found thoughts emphasizing visual imagery at rest were associated with dispositional tendency towards internally directed attention (self-consciousness and attentional problems) and linked to a stronger correlation between a posterior parietal network and a lateral fronto-temporal network. Furthermore, decoupling between the brainstem and a lateral visual network was associated with dispositional internally directed attention. Critically, these brain–cognition associations were related: the correlation between parietal–frontal regions and reports of visual imagery was stronger for individuals with increased connectivity between brainstem and visual cortex. Our results highlight neural mechanisms linked to the dispositional basis for patterns of self-generated thought, and suggest that accounting for dispositional traits is important when exploring the neural substrates of self-generated experience (and vice versa).This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation’.     

Functional Reorganization of the Default Mode Network across Chronic Pain Conditions

Chronic pain is associated with neuronal plasticity. Here we use resting-state functional magnetic resonance imaging to investigate functional changes in patients suffering from chronic back pain (CBP), complex regional pain syndrome (CRPS) and knee osteoarthritis (OA). We isolated five meaningful resting-state networks across the groups, of which only the default mode network (DMN) exhibited deviations from healthy controls. All patient groups showed decreased connectivity of medial prefrontal cortex (MPFC) to the posterior constituents of the DMN, and increased connectivity to the insular cortex in proportion to the intensity of pain. Multiple DMN regions, especially the MPFC, exhibited increased high frequency oscillations, conjoined with decreased phase locking with parietal regions involved in processing attention. Both phase and frequency changes correlated to pain duration in OA and CBP patients. Thus chronic pain seems to reorganize the dynamics of the DMN and as such reflect the maladaptive physiology of different types of chronic pain.     

Hierarchical Alteration of Brain Structural and Functional Networks in Female Migraine Sufferers

Background

Little is known about the changes of brain structural and functional connectivity networks underlying the pathophysiology in migraine. We aimed to investigate how the cortical network reorganization is altered by frequent cortical overstimulation associated with migraine.

Methodology/Principal Findings

Gray matter volumes and resting-state functional magnetic resonance imaging signal correlations were employed to construct structural and functional networks between brain regions in 43 female patients with migraine (PM) and 43 gender-matched healthy controls (HC) by using graph theory-based approaches. Compared with the HC group, the patients showed abnormal global topology in both structural and functional networks, characterized by higher mean clustering coefficients without significant change in the shortest absolute path length, which indicated that the PM lost optimal topological organization in their cortical networks. Brain hubs related to pain-processing revealed abnormal nodal centrality in both structural and functional networks, including the precentral gyrus, orbital part of the inferior frontal gyrus, parahippocampal gyrus, anterior cingulate gyrus, thalamus, temporal pole of the middle temporal gyrus and the inferior parietal gyrus. Negative correlations were found between migraine duration and regions with abnormal centrality. Furthermore, the dysfunctional connections in patients'' cortical networks formed into a connected component and three dysregulated modules were identified involving pain-related information processing and motion-processing visual networks.

Conclusions

Our results may reflect brain alteration dynamics resulting from migraine and suggest that long-term and high-frequency headache attacks may cause both structural and functional connectivity network reorganization. The disrupted information exchange between brain areas in migraine may be reshaped into a hierarchical modular structure progressively.     

Disrupted Structural and Functional Connectivity in Prefrontal-Hippocampus Circuitry in First-Episode Medication-Na?ve Adolescent Depression

Background

Evidence implicates abnormalities in prefrontal-hippocampus neural circuitry in major depressive disorder (MDD). This study investigates the potential disruptions in prefrontal-hippocampus structural and functional connectivity, as well as their relationship in first-episode medication-naïve adolescents with MDD in order to investigate the early stage of the illness without confounds of illness course and medication exposure.

Methods

Diffusion tensor imaging and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 26 first-episode medication-naïve MDD adolescents and 31 healthy controls (HC). Fractional anisotropy (FA) values of the fornix and the prefrontal-hippocampus functional connectivity was compared between MDD and HC groups. The correlation between the FA value of fornix and the strength of the functional connectivity in the prefrontal cortex (PFC) region showing significant differences between the two groups was identified.

Results

Compared with the HC group, adolescent MDD group had significant lower FA values in the fornix, as well as decreased functional connectivity in four PFC regions. Significant negative correlations were observed between fornix FA values and functional connectivity from hippocampus to PFC within the HC group. There was no significant correlation between the fornix FA and the strength of functional connectivity within the adolescent MDD group.

Conclusions

First-episode medication-naïve adolescent MDD showed decreased structural and functional connectivity as well as deficits of the association between structural and functional connectivity shown in HC in the PFC-hippocampus neural circuitry. These findings suggest that abnormal PFC-hippocampus neural circuitry may present in the early onset of MDD and play an important role in the neuropathophysiology of MDD.     

Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy

Idiopathic/genetic generalized epilepsy (IGE/GGE) is characterized by seizures, which start and rapidly engage widely distributed networks, and result in symptoms such as absences, generalized myoclonic and primary generalized tonic-clonic seizures. Although routine magnetic resonance imaging is apparently normal, many studies have reported structural alterations in IGE/GGE patients using diffusion tensor imaging and voxel-based morphometry. Changes have also been reported in functional networks during generalized spike wave discharges. However, network function in the resting-state without epileptiforme discharges has been less well studied. We hypothesize that resting-state networks are more representative of the underlying pathophysiology and abnormal network synchrony. We studied functional network connectivity derived from whole-brain magnetoencephalography recordings in thirteen IGE/GGE and nineteen healthy controls. Using graph theoretical network analysis, we found a widespread increase in connectivity in patients compared to controls. These changes were most pronounced in the motor network, the mesio-frontal and temporal cortex. We did not, however, find any significant difference between the normalized clustering coefficients, indicating preserved gross network architecture. Our findings suggest that increased resting state connectivity could be an important factor for seizure spread and/or generation in IGE/GGE, and could serve as a biomarker for the disease.     

Neural Mechanisms by Which Attention Modulates the Comparison of Remembered and Perceptual Representations

Attention is important for effectively comparing incoming perceptual information with the contents of visual short-term memory (VSTM), such that any differences can be detected. However, how attentional mechanisms operate upon these comparison processes remains largely unknown. Here we investigate the underlying neural mechanisms by which attention modulates the comparisons between VSTM and perceptual representations using functional magnetic resonance imaging (fMRI). Participants performed a cued change detection task. Spatial cues were presented to orient their attention either to the location of an item in VSTM prior to its comparison (retro-cues), or simultaneously (simultaneous-cues) with the probe array. A no-cue condition was also included. When attention cannot be effectively deployed in advance (i.e. following the simultaneous-cues), we observed a distributed and extensive activation pattern in the prefrontal and parietal cortices in support of successful change detection. This was not the case when participants can deploy their attention in advance (i.e. following the retro-cues). The region-of-interest analyses confirmed that neural responses for successful change detection versus correct rejection in the visual and parietal regions were significantly different for simultaneous-cues compared to retro-cues. Importantly, we found enhanced functional connectivity between prefrontal and parietal cortices when detecting changes on the simultaneous-cue trials. Moreover, we demonstrated a close relationship between this functional connectivity and d′ scores. Together, our findings elucidate the attentional and neural mechanisms by which items held in VSTM are compared with incoming perceptual information.     

Aberrant Resting-State Corticostriatal Functional Connectivity in Cirrhotic Patients with Hyperintense Globus Pallidus on T1-Weighted MR Imaging

Neurobiological and neuroimaging studies have emphasized the structural and functional alterations in the striatum of cirrhotic patients, but alterations in the functional connections between the striatum and other brain regions have not yet been explored. Of note, manganese accumulation in the nervous system, frequently reflected by hyperintensity at the bilateral globus pallidus (GP) on T1-weighted imaging, has been considered a factor affecting the striatal and cortical functions in hepatic decompensation. We employed resting-state functional magnetic resonance imaging to analyze the temporal correlation between the striatum and the remaining brain regions using seed-based correlation analyses. The two-sample t-test was conducted to detect the differences in corticostriatal connectivity between 44 cirrhotic patients with hyperintensity at the bilateral GP and 20 healthy controls. Decreased connectivity of the caudate was detected in the anterior/middle cingulate gyrus, and increased connectivity of the caudate was found in the left motor cortex. A reduction in functional connectivity was found between the putamen and several regions, including the anterior cingulate gyrus, right insular lobe, inferior frontal gyrus, left parahippocampal gyrus, and anterior lobe of the right cerebellum; increased connectivity was detected between the putamen and right middle temporal gyrus. There were significant correlations between the corticostriatal connectivity and neuropsychological performances in the patient group, but not between the striatal connectivity and GP signal intensity. These alterations in the corticostriatal functional connectivity suggested the abnormalities in the intrinsic brain functional organiztion among the cirrhotic patients with manganese deposition, and may be associated with development of metabolic encephalopathy. The manganese deposition in nervous system, however, can not be an independent factor predicting the resting-state brain dysfunction in real time.