Structural and resting state functional connectivity beyond the cortex.
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ABSTRACT:
SUBMITTER: Harrison OK
PROVIDER: S-EPMC8429261 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks--including their spatial statistics and their persistence across time--can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.
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Project description:The medial superior frontal cortex (SFC), including the supplementary motor area (SMA) and presupplementary motor area (preSMA), is implicated in movement and cognitive control, among other functions central to decision making. Previous studies delineated the anatomical boundaries and functional connectivity of the SMA. However, it is unclear whether the preSMA, which responds to a variety of behavioral tasks, comprises functionally distinct areas. With 24 seed regions systematically demarcated throughout the anterior and posterior medial SFC, we examined here the functional divisions of the medial SFC on the basis of the "correlograms" of resting-state functional magnetic resonance imaging data of 225 adult individuals. In addition to replicating segregation of the SMA and posterior preSMA, the current results elucidated functional connectivities of anterior preSMA-the most anterior part of the medial SFC. In contrast to the caudal medial SFC, the anterior preSMA is connected with most of the prefrontal but not with somatomotor areas. Overall, the SMA is strongly connected to the thalamus and epithalamus, the posterior preSMA to putamen, pallidum, and subthalamic nucleus, and anterior preSMA to the caudate, with the caudate showing significant hemispheric asymmetry. These findings may provide a useful platform for future studies to investigate frontal cortical functions.
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Project description:BackgroundVery few studies have been performed to understand the underlying neural substrates of adolescent major depressive disorder (MDD). Studies in depressed adults have demonstrated that the subgenual anterior cingulate cortex (sgACC) plays a pivotal role in depression and have revealed aberrant patterns of resting-state functional connectivity (RSFC). Here, we examine the RSFC of the sgACC in medication-naïve first-episode adolescents with MDD.MethodsTwenty-three adolescents with MDD and 36 well-matched control subjects underwent functional magnetic resonance imaging to assess the RSFC of the sgACC.ResultsWe observed elevated connectivity between the sgACC and the insula and between the sgACC and the amygdala in the MDD group compared with the control subjects. Decreased connectivity between the sgACC and the precuneus was also found in the MDD group relative to the control subjects. Within the MDD group, higher levels of depression significantly correlated with decreased connectivity between the sgACC and left precuneus. Increased rumination was significantly associated with reduced connectivity between sgACC and the middle and inferior frontal gyri in the MDD group.ConclusionsOur study is the first to examine sgACC connectivity in medication-naïve first-episode adolescents with MDD compared with well-matched control participants. Our results suggest aberrant functional connectivity among the brain networks responsible for salience attribution, executive control, and the resting-state in the MDD group compared with the control participants. Our findings raise the possibility that therapeutic interventions that can restore the functional connectivity among these networks to that typical of healthy adolescents might be a fruitful avenue for future research.
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Project description:BackgroundPatients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown.MethodsUsing a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity.ResultsRelative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network.ConclusionsThese results are opposite to that which we found with 7 days treatment of citalopram in healthy volunteers. These results reflect a different mechanism of action of bupropion compared with selective serotonergic reuptake inhibitors. These results help explain the apparent lack of emotional blunting caused by bupropion in depressed patients.
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Project description:Studies of resting-state activity in the brain have provoked critical questions about the brain's functional organization, but the biological basis of this activity is not clear. Specifically, the relationships between interregional correlations in resting-state measures of activity, neuronal functional connectivity and anatomical connectivity are much debated. To investigate these relationships, we have examined both anatomical and steady-state functional connectivity within the hand representation of primary somatosensory cortex (areas 3b and 1) in anesthetized squirrel monkeys. The comparison of three data sets (fMRI, electrophysiological, and anatomical) indicate two primary axes of information flow within the SI: prominent interdigit interactions within area 3b and predominantly homotopic interactions between area 3b and area 1. These data support a strikingly close relationship between baseline functional connectivity and anatomical connections. This study extends findings derived from large-scale cortical networks to the realm of local millimeter-scale networks.
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Project description:Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function.
| S-EPMC5761874 | biostudies-literature
Project description:The relationship between structural and functional connectivity has been mostly examined in intact brains. Fewer studies have examined how differences in structure as a result of injury alters function. In this study we analyzed the relationship of structure to function across patients with stroke among whom infarcts caused heterogenous structural damage. We estimated relationships between distinct brain regions of interest (ROIs) from functional MRI in two pipelines. In one analysis pipeline, we measured functional connectivity by using correlation and partial correlation between 114 cortical ROIs. We found fMRI-BOLD partial correlation was altered at more edges as a function of the structural connectome (SC) damage, relative to the correlation. In a second analysis pipeline, we limited our analysis to fMRI correlations between pairs of voxels for which we possess SC information. We found that voxel-level functional connectivity showed the effect of structural damage that we could not see when examining correlations between ROIs. Further, the effects of structural damage on functional connectivity are consistent with a model of functional connectivity, diffusion, which expects functional connectivity to result from activity spreading over multiple edge anatomical paths.
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Project description: Not available
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Project description:Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).
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Project description:BackgroundNeuroimaging studies in late life depression have reported decreased structural integrity of white matter tracts in the prefrontal cortex. Functional studies have identified changes in functional connectivity among several key areas involved in mood regulation. Few studies have combined structural and functional imaging. In this study we sought to examine the relationship between the uncinate fasciculus, a key fronto-temporal tract and resting state functional connectivity between the ventral prefrontal cortex ((PFC) and limbic and striatal areas.MethodsThe sample consisted of 24 older patients remitted from unipolar major depression. Each participant had a magnetic resonance imaging brain scan using standardized protocols to obtain both diffusion tensor imaging and resting state functional connectivity data. Our statistical approach compared structural integrity of the uncinate fasciculus and functional connectivity data.ResultsWe found positive correlations between left uncinate fasciculus (UF) fractional anisotropy (FA) and resting state functional connectivity (rsFC) between the left ventrolateral PFC and left amygdala and between the left ventrolateral PFC and the left hippocampus. In addition, we found a significant negative correlation between left ventromedial PFC-caudate rsFC and left UF FA. The right UF FA did not correlate with any of the seed region based connectivity.ConclusionsThese results support the notion that resting state functional connectivity reflects structural integrity, since the ventral PFC is structurally connected to temporal regions by the UF. Future studies should include larger samples of patients and healthy comparison subjects in which both resting state and task-based functional connectivity are examined.
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