Resting-state Functional Connectivity Maps Research Articles

Increased interhemispheric resting-state functional connectivity after sleep deprivation: a resting-state fMRI study.

Several functional imaging studies have investigated the regional effects of sleep deprivation (SD) on impaired brain function; however, potential changes in the functional interactions between the cerebral hemispheres after SD are not well understood. In this study, we used a recently validated approach, voxel-mirrored homotopic connectivity (VMHC), to directly examine the changes in interhemispheric homotopic resting-state functional connectivity (RSFC) after SD. Resting-state functional MRI (fMRI) was performed in 28 participants both after rest wakefulness (RW) and a total night of SD. An interhemispheric RSFC map was obtained by calculating the Pearson correlation (Fisher Z transformed) between each pair of homotopic voxel time series for each subject in each condition. The between-condition differences in interhemispheric RSFC were then examined at global and voxelwise levels separately. Significantly increased global VMHC was found after sleep deprivation; specifically, a significant increase in VMHC was found in specific brain regions, including the thalamus, paracentral lobule, supplementary motor area, postcentral gyrus and lingual gyrus. No regions showed significantly reduced VMHC after sleep deprivation. Further analysis indicates that these findings did not depend on the various sizes of smoothing kernels that were adopted in the preprocessing steps and that the differences in these regions were still significant with or without global signal regression. Our data suggest that the increased VMHC might reflect the compensatory involvement of bilateral brain areas, especially the bilateral thalamus, to prevent cognitive performance deterioration when sleep pressure is elevated after sleep deprivation. Our findings provide preliminary evidence of interhemispheric correlation changes after SD and contribute to a better understanding of the neural mechanisms of SD.

Increased interhemispheric resting-state in idiopathic generalized epilepsy with generalized tonic–clonic seizures: A resting-state fMRI study

The aim is to examine the resting state functional connectivity (RSFC) between the two hemispheres and its relationships with clinical characteristic in idiopathic generalized epilepsy with generalized tonic-clonic seizures only (IGE-GTCS) patients using a technique called "voxel-mirrored homotopic connectivity (VMHC)". The resting-state functional MRI (Rs-fMRI) was used to measure the RSFC in patients with IGE-GTC and age-gender matched healthy subjects. The between-group difference in interhemispheric RSFC was examined after the interhemispheric RSFC map was obtained by an automated VMHC approach. Compared to the controls, the IGE-GTCS patients showed significant increases in VMHC in the bilateral anterior cingulate and medial prefrontal gyrus. No areas showed decreased VMHC in patients. Moreover, the VMHC in bilateral thalamus, orbital frontal cortex as well as cerebellum showed significant negative correlations with the illness duration. The current findings provide preliminary evidence of increased interhemispheric RSFC in patients with IGE-GTCS during the interictal period. These VMHC deficits in these regions and the inverse relations between VMHC and clinical characteristic may play an important role in the pathophysiology of IGE-GTCS. Our study may contribute to the understanding of neuro-pathophysiological mechanism of epilepsy and psychosocial function impairments in patients with IGE-GTCS.

The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis.

The right temporoparietal junction (rTPJ) is frequently associated with different capacities that to shift attention to unexpected stimuli (reorienting of attention) and to understand others' (false) mental state [theory of mind (ToM), typically represented by false belief tasks]. Competing hypotheses either suggest the rTPJ representing a unitary region involved in separate cognitive functions or consisting of subregions subserving distinct processes. We conducted activation likelihood estimation (ALE) meta-analyses to test these hypotheses. A conjunction analysis across ALE meta-analyses delineating regions consistently recruited by reorienting of attention and false belief studies revealed the anterior rTPJ, suggesting an overarching role of this specific region. Moreover, the anatomical difference analysis unravelled the posterior rTPJ as higher converging in false belief compared with reorienting of attention tasks. This supports the concept of an exclusive role of the posterior rTPJ in the social domain. These results were complemented by meta-analytic connectivity mapping (MACM) and resting-state functional connectivity (RSFC) analysis to investigate whole-brain connectivity patterns in task-constrained and task-free brain states. This allowed for detailing the functional separation of the anterior and posterior rTPJ. The combination of MACM and RSFC mapping showed that the posterior rTPJ has connectivity patterns with typical ToM regions, whereas the anterior part of rTPJ co-activates with the attentional network. Taken together, our data suggest that rTPJ contains two functionally fractionated subregions: while posterior rTPJ seems exclusively involved in the social domain, anterior rTPJ is involved in both, attention and ToM, conceivably indicating an attentional shifting role of this region.

Morphological brain plasticity induced by musical expertise is accompanied by modulation of functional connectivity at rest

The aim of this study was to explore whether musical practice-related gray matter increases in brain regions are accompanied by modifications in their resting-state functional connectivity. 16 young musically experienced adults and 17 matched nonmusicians underwent an anatomical magnetic resonance imaging (MRI) and a resting-state functional MRI (rsfMRI). A whole-brain two-sample t test run on the T1-weighted structural images revealed four clusters exhibiting significant increases in gray matter (GM) volume in the musician group, located within the right posterior and middle cingulate gyrus, left superior temporal gyrus and right inferior orbitofrontal gyrus. Each cluster was used as a seed region to generate and compare whole-brain resting-state functional connectivity maps. The two clusters within the cingulate gyrus exhibited greater connectivity for musicians with the right prefrontal cortex and left temporal pole, which play a role in autobiographical and semantic memory, respectively. The cluster in the left superior temporal gyrus displayed enhanced connectivity with several language-related areas (e.g., left premotor cortex, bilateral supramarginal gyri). Finally, the cluster in the right inferior frontal gyrus displayed more synchronous activity at rest with claustrum, areas thought to play a role in binding sensory and motor information. We interpreted these findings as the consequence of repeated collaborative use in general networks supporting some of the memory, perceptual-motor and emotional features of musical practice.

Increased interhemispheric resting‐state functional connectivity in functional dyspepsia: a pilot study

Recent brain imaging studies have emphasized the role of regional brain activity abnormalities in the pathophysiology of functional dyspepsia (FD). However, whether the functional connectivity between brain regions is changed, especially between the cerebral hemispheres, in patients with FD remains unknown. Thus, the present study aimed to examine the interhemispheric resting-state functional connectivity (RSFC) changes in patients with FD. Resting-state functional MRI (fMRI) was performed in 26 patients with FD and in 20 matched healthy controls. An interhemispheric RSFC map was obtained by calculating the Pearson correlation (Fisher Z transformed) between each pair of homotopic voxel time series for each subject. The between-group difference in interhemispheric RSFC was then examined at global and voxelwise levels separately. The global difference in interhemispheric RSFC between groups was tested using the independent two-sample t-test. Voxelwise comparisons were carried out using a permutation-based nonparametric test, and multiple comparisons across space were corrected using the threshold-free cluster enhancement (TFCE) method. The results showed that patients with FD had higher global interhemispheric RSFC than healthy controls (p < 0.01). Furthermore, voxelwise analysis revealed that patients with FD had increased interhemispheric RSFC in brain regions including the anterior cingulate cortex, insula and thalamus (p < 0.01, TFCE corrected). Our findings provide preliminary evidence of interhemispheric correlation abnormalities in patients with FD and contribute to a better understanding of the pathophysiology of the disease.

Resting-State Functional Connectivity Patterns Predict Chinese Word Reading Competency

Resting-state functional connectivity (RSFC) offers a novel approach to reveal the temporal synchronization of functionally related brain regions. Recent studies have identified several RSFCs whose strength was associated with reading competence in alphabetic languages. In the present study, we examined the role of intrinsic functional relations for reading a non-alphabetic language – Chinese – by correlating RSFC maps of nine Chinese reading-related seed regions and reaction time in the single-character reading task. We found that Chinese reading efficiency was positively correlated with the connection between left inferior occipital gyrus and left superior parietal lobule, between right posterior fusiform gyrus and right superior parietal lobule, and between left inferior temporal gyrus and left inferior parietal lobule. These results could not be attributed to inter-individual differences arising from the peripheral processes of the reading task such as visual input detection and articulation. The observed RSFC-reading correlation relationships are discussed in the framework of Chinese character reading, including visuospatial analyses and semantic/phonological processes.

Resting state functional-connectivity mapping of putative visual cortex in a blind patient

Resting state functional-connectivity mapping of putative visual cortex in a blind patient

Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study

The feasibility of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (RSFC) has already been demonstrated. However the validity of fNIRS-based RSFC has rarely been studied. In the present study, fNIRS and fMRI data were simultaneously acquired from 21 subjects during the resting state. After the spatial correspondence was established between the two imaging modalities by transforming the fMRI data into fNIRS measurements space, the index of Between-Modality-Similarity (BMS) of RSFC was evaluated across multiple spatial scales. First, the RSFC between the bilateral primary motor ROI was quite similar between fNIRS and fMRI for all the subjects (BMSROI=0.95±0.04 for HbO and BMSROI=0.86±0.13 for HbR). Second, group-level sensorimotor RSFC maps (0.79 for HbO and 0.74 for HbR) showed higher between-modality similarity than individual-level RSFC maps (0.48±0.16 for HbO and 0.41±0.15 for HbR). Finally, for the first time, we combined fNIRS and graph theory to investigate topological properties of resting-state brain networks. The clustering coefficient (Cp) and characteristic path length (Lp) which are the most important network topological parameters, both showed high between-modality similarities (BMSCp=0.90±0.03 for HbO and 0.90±0.06 for HbR; BMSLp=0.92±0.04 for HbO and 0.91±0.05 for HbR). In summary, the converged results across all the spatial scales demonstrated that fNIRS is capable of providing comparable RSFC measures to fMRI, and thus provide direct evidence for the validity of the optical brain connectivity and the optical brain network approaches to functional brain integration during resting state.

Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches

The cognitive activity of the human brain benefits from the functional connectivity of multiple brain regions that form specific, functional brain networks. Recent studies have indicated that the relationship between brain regions can be investigated by examining the temporal interaction (known as functional connectivity) of spontaneous blood oxygen level-dependent (BOLD) signals derived from resting-state functional MRI. Most of these studies plausibly assumed that inter-regional interactions were temporally stationary. However, little is known about the dynamic characteristics of resting-state functional connectivity (RSFC). In this study, we thoroughly examined this question within and between multiple functional brain networks. Twenty-two healthy subjects were scanned in a resting state. Several of the RSFC networks observed, including the default-mode, motor, attention, memory, auditory, visual, language and subcortical networks, were first identified using a conventional voxel-wise correlation analysis with predefined region of interests (ROIs). Then, a variable parameter regression model combined with the Kalman filtering method was employed to detect the dynamic interactions between each ROI and all other brain voxels within each of the RSFC maps extracted above. Experimental results revealed that the functional interactions within each RSFC map showed time-varying properties, and that approximately 10–20% of the voxels within each RSFC map showed significant functional connectivity to each ROI during the scanning session. This dynamic pattern was also observed for the interactions between different functional networks. In addition, the spatial pattern of dynamic connectivity maps obtained from neighboring time points had a high similarity. Overall, this study provides insights into the dynamic properties of resting-state functional networks.

Imaging of Functional Connectivity in the Mouse Brain

Functional neuroimaging (e.g., with fMRI) has been difficult to perform in mice, making it challenging to translate between human fMRI studies and molecular and genetic mechanisms. A method to easily perform large-scale functional neuroimaging in mice would enable the discovery of functional correlates of genetic manipulations and bridge with mouse models of disease. To satisfy this need, we combined resting-state functional connectivity mapping with optical intrinsic signal imaging (fcOIS). We demonstrate functional connectivity in mice through highly detailed fcOIS mapping of resting-state networks across most of the cerebral cortex. Synthesis of multiple network connectivity patterns through iterative parcellation and clustering provides a comprehensive map of the functional neuroarchitecture and demonstrates identification of the major functional regions of the mouse cerebral cortex. The method relies on simple and relatively inexpensive camera-based equipment, does not require exogenous contrast agents and involves only reflection of the scalp (the skull remains intact) making it minimally invasive. In principle, fcOIS allows new paradigms linking human neuroscience with the power of molecular/genetic manipulations in mouse models.

Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy

Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high-level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach.

Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements

As a promising non-invasive imaging technique, functional near infrared spectroscopy (fNIRS) has recently earned increasing attention in resting-state functional connectivity (RSFC) studies. Preliminary fNIRS-based RSFC studies adopted a seed correlation approach and yielded interesting results. However, the seed correlation approach has several inherent problems, such as neglecting of interactions among multiple regions and a dependence on seed region selection. Moreover, ineffectively reduced noise and artifacts in fNIRS measurements also negatively affect RSFC results. In this study, independent component analysis (ICA) was introduced to meet these challenges in RSFC detection based on resting-state fNIRS measurements. The results of ICA on data from the sensorimotor and the visual systems both showed functional system-specific RSFC maps. Results from comparison between ICA and the conventional seed correlation approach demonstrated, both qualitatively and quantitatively, the superior performance of ICA with higher sensitivity and specificity, especially in the case of higher noise level. The capability of ICA to separate noise and artifacts from resting-state fNIRS data was also demonstrated, and the extracted noise and artifacts were illustrated. Finally, some practical issues on performing ICA on resting-state fNIRS data were discussed.

Use of fNIRS to assess resting state functional connectivity

Recently, resting state functional connectivity (RSFC) studies based on fMRI and EEG/MEG have provided valuable insight into the intrinsic functional architecture of the human brain. However, whether functional near infrared spectroscopy (fNIRS), a suitable imaging method for infant and patient populations, can be used to examine RSFC remains elusive. Using an ETG-4000 Optical Topography System, the present study measured 29 adult subjects (14 females) over the sensorimotor and auditory cortexes during a resting session and a motor-localizer task session. The RSFC maps were computed by seed-based correlation analysis and data-driven cluster analysis. The results from both analyses showed robust RSFC maps, which were not only consistent with the localizer task-related activation results, but also those of previous fMRI findings. Moreover, the strong consistency between the seed-based correlation analysis and the data-driven cluster analysis further validated the use of fNIRS to assess RSFC. The potential influence of a specific low-frequency filtering range (0.04–0.15 Hz and 0.01–0.08 Hz) and three fNIRS parameters (oxy-Hb, deoxy-Hb, and total-Hb) on RSFC results were also examined.

Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network

Resting-state functional connectivity magnetic resonance imaging (fcMRI) studies constitute a growing proportion of functional brain imaging publications. This approach detects temporal correlations in spontaneous blood oxygen level-dependent (BOLD) signal oscillations while subjects rest quietly in the scanner. Although distinct resting-state networks related to vision, language, executive processing, and other sensory and cognitive domains have been identified, considerable skepticism remains as to whether resting-state functional connectivity maps reflect neural connectivity or simply track BOLD signal correlations driven by nonneural artifact. Here we combine diffusion tensor imaging (DTI) tractography with resting-state fcMRI to test the hypothesis that resting-state functional connectivity reflects structural connectivity. These 2 modalities were used to investigate connectivity within the default mode network, a set of brain regions--including medial prefrontal cortex (MPFC), medial temporal lobes (MTLs), and posterior cingulate cortex (PCC)/retropslenial cortex (RSC)--implicated in episodic memory processing. Using seed regions from the functional connectivity maps, the DTI analysis revealed robust structural connections between the MTLs and the retrosplenial cortex whereas tracts from the MPFC contacted the PCC (just rostral to the RSC). The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks.

134 ERD/ERS based brain computer interface (BCI): Effects of motor imagery on sensorimotor rhythms

The aim is to examine the resting state functional connectivity (RSFC) between the two hemispheres and its relationships with clinical characteristic in idiopathic generalized epilepsy with generalized tonic–clonic seizures only (IGE-GTCS) patients using a technique called “voxel-mirrored homotopic connectivity (VMHC)”.The resting-state functional MRI (Rs-fMRI) was used to measure the RSFC in patients with IGE-GTC and age–gender matched healthy subjects. The between-group difference in interhemispheric RSFC was examined after the interhemispheric RSFC map was obtained by an automated VMHC approach.Compared to the controls, the IGE-GTCS patients showed significant increases in VMHC in the bilateral anterior cingulate and medial prefrontal gyrus. No areas showed decreased VMHC in patients. Moreover, the VMHC in bilateral thalamus, orbital frontal cortex as well as cerebellum showed significant negative correlations with the illness duration.The current findings provide preliminary evidence of increased interhemispheric RSFC in patients with IGE-GTCS during the interictal period. These VMHC deficits in these regions and the inverse relations between VMHC and clinical characteristic may play an important role in the pathophysiology of IGE-GTCS. Our study may contribute to the understanding of neuro-pathophysiological mechanism of epilepsy and psychosocial function impairments in patients with IGE-GTCS.

Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps

We have recently demonstrated using functional magnetic resonance imaging the presence of synchronous low-frequency fluctuations of signal intensities from the resting human brain that have a high degree of temporal correlation (p < 0.0001) both within and across the sensorimotor cortex. A statistically significant overlap between the resting-state functional connectivity map and the task-activation map due to bilateral finger tapping was obtained. Similar results have been obtained in the auditory and visual cortex. Because the pulse sequence used for collecting data was sensitive to blood flow and blood oxygenation, these low-frequency fluctuations of signal intensity may have arisen from variations of both. The objective of this study was simultaneously to determine the contribution of the blood oxygenation level signal and the flow signal to physiological fluctuations in the resting brain using the flow-sensitive alternating inversion recovery pulse sequence. In all subjects, the functional connectivity maps obtained from BOLD had a greater coincidence with task-activation maps than the corresponding functional connectivity maps obtained from blood-flow signals at the same level of statistical significance. Results of this study suggest that while variations in blood flow might contribute to functional connectivity maps, BOLD signals play a dominant role in the mechanism that gives rise to functional connectivity in the resting human brain.