In this paper, we present a groupwise graph-theory-based parcellation approach to define nodes for network analysis. The application of network-theory-based analysis to extend the utility of ...functional MRI has recently received increased attention. Such analyses require first and foremost a reasonable definition of a set of nodes as input to the network analysis. To date many applications have used existing atlases based on cytoarchitecture, task-based fMRI activations, or anatomic delineations. A potential pitfall in using such atlases is that the mean timecourse of a node may not represent any of the constituent timecourses if different functional areas are included within a single node. The proposed approach involves a groupwise optimization that ensures functional homogeneity within each subunit and that these definitions are consistent at the group level. Parcellation reproducibility of each subunit is computed across multiple groups of healthy volunteers and is demonstrated to be high. Issues related to the selection of appropriate number of nodes in the brain are considered. Within typical parameters of fMRI resolution, parcellation results are shown for a total of 100, 200, and 300 subunits. Such parcellations may ultimately serve as a functional atlas for fMRI and as such three atlases at the 100-, 200- and 300-parcellation levels derived from 79 healthy normal volunteers are made freely available online along with tools to interface this atlas with SPM, BioImage Suite and other analysis packages.
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•Resting-state connectivity data parcellated using graph theory approach.•Yields groupwise whole-brain parcellation of the order of 300 nodes•Uniform timecourses within nodes•Ideal for network analysis of functional connectivity•Functional atlas available online
Resting-state fMRI provides a method to examine the functional network of the brain under spontaneous fluctuations. A number of studies have proposed using resting-state BOLD data to parcellate the ...brain into functional subunits. In this work, we present two state-of-the-art graph-based partitioning approaches, and investigate their application to the problem of brain network segmentation using resting-state fMRI. The two approaches, the normalized cut (Ncut) and the modularity detection algorithm, are also compared to the Gaussian mixture model (GMM) approach. We show that the Ncut approach performs consistently better than the modularity detection approach, and it also outperforms the GMM approach for in vivo fMRI data. Resting-state fMRI data were acquired from 43 healthy subjects, and the Ncut algorithm was used to parcellate several different cortical regions of interest. The group-wise delineation of the functional subunits based on resting-state fMRI was highly consistent with the parcellation results from two task-based fMRI studies (one with 18 subjects and the other with 20 subjects). The findings suggest that whole-brain parcellation of the cortex using resting-state fMRI is feasible, and that the Ncut algorithm provides the appropriate technique for this task.
•Open preprocessing pipeline for dual wavelength mesoscale calcium imaging•Overall functional architecture persists across brain states and cell types•Seed-based connectivity and graph theory reveal ...more subtle differences
To improve ‘bench-to-bedside’ translation, it is integral that knowledge flows bidirectionally—from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data—an emerging mode applicable in animal models—as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.
Anxiety is a core human emotion but can become pathologically dysregulated. We used functional magnetic resonance imaging (fMRI) neurofeedback (NF) to noninvasively alter patterns of brain ...connectivity, as measured by resting-state fMRI, and to reduce contamination anxiety. Activity of a region of the orbitofrontal cortex associated with contamination anxiety was measured in real time and provided to subjects with significant but subclinical anxiety as a NF signal, permitting them to learn to modulate the target brain region. NF altered network connectivity of brain regions involved in anxiety regulation: subjects exhibited reduced resting-state connectivity in limbic circuitry and increased connectivity in the dorsolateral prefrontal cortex. NF has been shown to alter brain connectivity in other contexts, but it has been unclear whether these changes persist; critically, we observed changes in connectivity several days after the completion of NF training, demonstrating that such training can lead to lasting modifications of brain functional architecture. Training also increased subjects' control over contamination anxiety several days after the completion of NF training. Changes in resting-state connectivity in the target orbitofrontal region correlated with these improvements in anxiety. Matched subjects undergoing a sham feedback control task showed neither a reorganization of resting-state functional connectivity nor an improvement in anxiety. These data suggest that NF can enable enhanced control over anxiety by persistently reorganizing relevant brain networks and thus support the potential of NF as a clinically useful therapy.
Resting-state fMRI (rs-fMRI) holds promise as a clinical tool to characterize and monitor the phenotype of different neurological and psychiatric disorders. The most common analysis approach requires ...the definition of one or more regions-of-interest (ROIs). However this need for a priori ROI information makes rs-fMRI inadequate to survey functional connectivity differences associated with a range of neurological disorders where the ROI information may not be available. A second problem encountered in fMRI measures of connectivity is the need for an arbitrary correlation threshold to determine whether or not two areas are connected. This is problematic because in many cases the differences in tissue connectivity between disease groups and/or control subjects are threshold dependent. In this work we propose a novel voxel-based contrast mechanism for rs-fMRI, the intrinsic connectivity distribution (ICD), that neither requires a priori information to define a ROI, nor an arbitrary threshold to define a connection. We show the sensitivity of previous methods to the choice of connection thresholds and evaluate ICD using a survey study comparing young adults born prematurely to healthy term control subjects. Functional connectivity differences were found in hypothesized language processing areas in the left temporal–parietal areas. In addition, significant clinically-relevant differences were found between preterm and term control subjects, highlighting the importance of whole brain surveys independent of a priori information.
► We devised a novel metric to detect differences in functional connectivity. ► Intrinsic Connectivity Distribution (ICD) models voxel connection distributions. ► Unlike the network measure degree, ICD does not require a connection threshold. ► ICD is an exploratory tool that probes local tissue connectivity and organization. ► ICD revealed differences between preterm and term subjects not identified by degree.
Statistical models have shown considerable promise as a basis for segmenting and interpreting cardiac images. While a variety of statistical models have been proposed to improve the segmentation ...results, most of them are either static models (SMs), which neglect the temporal dynamics of a cardiac sequence, or generic dynamical models (GDMs), which are homogeneous in time and neglect the intersubject variability in cardiac shape and deformation. In this paper, we develop a subject-specific dynamical model (SSDM) that simultaneously handles temporal dynamics (intrasubject variability) and intersubject variability. We also propose a dynamic prediction algorithm that can progressively identify the specific motion patterns of a new cardiac sequence based on the shapes observed in past frames. The incorporation of this SSDM into the segmentation framework is formulated in a recursive Bayesian framework. It starts with a manual segmentation of the first frame, and then segments each frame according to intensity information from the current frame as well as the prediction from past frames. In addition, to reduce error propagation in sequential segmentation, we take into account the periodic nature of cardiac motion and perform segmentation in both forward and backward directions. We perform ¿leave-one-out¿ test on 32 canine sequences and 22 human sequences, and compare the experimental results with those from SM, GDM, and active appearance motion model (AAMM). Quantitative analysis of the experimental results shows that SSDM outperforms SM, GDM, and AAMM by having better global and local consistencies with manual segmentation. Moreover, we compare the segmentation results from forward and forward-backward segmentation. Quantitative evaluation shows that forward-backward segmentation suppresses the propagation of segmentation errors.
Myocardial infarction (MI) produces acute changes in strain and stiffness within the infarct that can affect remote areas of the left ventricle (LV) and drive pathological remodeling. We hypothesized ...that intramyocardial delivery of a hydrogel within the MI region would lower wall stress and reduce adverse remodeling in Yorkshire pigs (n = 5). 99mTc-Tetrofosmin SPECT imaging defined the location and geometry of induced MI and border regions in pigs, and in vivo and ex vivo contrast cine computed tomography (cineCT) quantified deformations of the LV myocardium. Serial in vivo cineCT imaging provided data in hearts from control pigs (n = 3) and data from pigs (n = 5) under baseline conditions before MI induction, post-MI day 3, post-MI day 7, and one hour after intramyocardial delivery of a hyaluronic acid (HA)-based hydrogel with shear-thinning and self-healing properties to the central infarct area. Isolated, excised hearts underwent similar cineCT imaging using an ex vivo perfused heart preparation with cyclic LV pressurization. Deformations were evaluated using nonlinear image registration of cineCT volumes between end-diastole (ED) and end-systole (ES), and 3D Lagrangian strains were calculated from the displacement gradients. Post-MI day 3, radial, circumferential, maximum principal, and shear strains were reduced within the MI region (p < 0.04) but were unchanged in normal regions (p > 0.6), and LV end diastolic volume (LV EDV) increased (p = 0.004), while ejection fraction (EF) and stroke volume (SV) decreased (p < 0.02). Post-MI day 7, radial strains in MI border zones increased (p = 0.04) and dilation of LV EDV continued (p = 0.052). There was a significant negative linear correlation between regional radial and maximum principal/shear strains and percent infarcted tissue in all hearts (R2 > 0.47, p < 0.004), indicating that cineCT strain measures could predict MI location and degree of injury. Post-hydrogel day 7 post-MI, LV EDV was significantly reduced (p = 0.009), EF increased (p = 0.048), and radial (p = 0.021), maximum principal (p = 0.051), and shear strain (p = 0.047) increased within regions bordering the infarct. A smaller strain improvement within the infarct and normal regions was also noted on average along with an improvement in SV in 4 out of 5 hearts. CineCT provides a reliable method to assess regional changes in strains post-MI and the therapeutic effects of intramyocardial hydrogel delivery.
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•Developed novel platform to assess left ventricle deformation in vivo and ex vivo.•Local cardiac strains decreased progressively over 7 days in infarcted regions.•Measured linear correlation between local degree of infarction and strain.•Hydrogel injection improved strain in regions bordering the infarct.•Hydrogel injection resulted in less ventricle dilation and larger ejection fraction.
Studies of working memory load effects on human EEG power have indicated divergent effects in different frequency bands. Although gamma power typically increases with load, the load dependency of the ...lower frequency theta and alpha bands is uncertain. We obtained intracranial electroencephalography measurements from 1453 electrode sites in 14 epilepsy patients performing a Sternberg task, in order to characterize the anatomical distribution of load-related changes across the frequency spectrum. Gamma power increases occurred throughout the brain, but were most common in the occipital lobe. In the theta and alpha bands, both increases and decreases were observed, but with different anatomical distributions. Increases in theta and alpha power were most prevalent in frontal midline cortex. Decreases were most commonly observed in occipital cortex, colocalized with increases in the gamma range, but were also detected in lateral frontal and parietal regions. Spatial overlap with group functional magnetic resonance imaging results was minimal except in the precentral gyrus. These findings suggest that power in any given frequency band is not a unitary phenomenon; rather, reactivity in the same frequency band varies in different brain regions, and may relate to the engagement or inhibition of a given area in a cognitive task.
The quantitative estimation of regional cardiac deformation from three-dimensional (3-D) image sequences has important clinical implications for the assessment of viability in the heart wall. We ...present here a generic methodology for estimating soft tissue deformation which integrates image-derived information with biomechanical models, and apply it to the problem of cardiac deformation estimation. The method is image modality independent. The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using a transversely isotropic, linear-elastic model, which accounts for the muscle fiber directions in the left ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strain in cardiac specific directions. The strains obtained using this approach in open-chest dogs before and after coronary occlusion, exhibit a high correlation with strains produced in the same animals using implanted markers. Further, they show good agreement with previously published results in the literature. This proposed method provides quantitative regional 3-D estimates of heart deformation.
Objective/Background To evaluate the feasibility and repeatability of applying blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) in the feet to quantify regional dynamic changes in ...tissue oxygenation during proximal cuff occlusion and reactive hyperemia. Methods Ten healthy male subjects underwent BOLD and T1-weighted imaging of the feet on two separate occasions, using a 3-T scanner. Dynamic changes in BOLD signal intensity were assessed before and during proximal cuff occlusion of the thigh and during reactive hyperemia, and BOLD time course data were evaluated for the time-to-half ischemic minimum, minimum ischemic value, peak hyperemic value, time-to-peak hyperemia, time-to-half peak hyperemia, and end value. T1-weighted images were used for segmentation of volumes of interest (VOI) in anatomical regions of the foot (heel, toes, dorsal foot, medial and lateral plantar foot). Repeatability of vascular responses was assessed for each foot VOI using semiautomated image registration and quantification of serial BOLD images. Results The heel VOI demonstrated a significantly higher peak hyperemic response, expressed as percent change from baseline BOLD signal intensity, compared with all other VOIs of the foot (heel, 7.4 ± 1.2%; toes, 5.6 ± 0.8%; dorsal foot, 5.7 ± 1.6%; medial plantar, 5.6 ± 1.7%; lateral plantar, 5.6 ± 1.5% p < .05). Additionally, the lateral plantar VOI had a significantly lower terminal signal intensity value (i.e., end value) when compared with all foot VOIs ( p < .05). BOLD MRI was repeatable between visits in all foot VOIs, with no significant differences between study visits for any of the evaluated functional indices. Conclusion BOLD MRI offers a repeatable technique for volumetric assessment of regional foot tissue oxygenation. Future application of BOLD imaging in the feet of patients with peripheral vascular disease may permit serial evaluation of regional tissue oxygenation and allow for improved assessment of therapeutic interventions targeting specific sites of the foot.
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