A Whole-Cortex Probabilistic Diffusion Tractography Connectome.
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ABSTRACT:
SUBMITTER: Rosen BQ
PROVIDER: S-EPMC7920542 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.
| S-EPMC6150949 | biostudies-literature
Project description:Diffusion-weighted neuroimaging approaches provide rich evidence for estimating the structural integrity of white matter in vivo, but typically do not assess white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon predefined regions of interest. Our approach derives a population distribution using probabilistic tractography, based on the Nathan Kline Institute (NKI) Enhanced Rockland sample. We determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and the fraction of diffusion directed along this orientation for each participant. The resulting participant-wise metrics (tract-specific anisotropy; TSA) can then be used for statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the "default mode" and "what-where" networks), along with more moderate sex differences and age-by-sex interactions. The proposed method can be applied to any arbitrary set of brain regions, to estimate both the spatial trajectory and DWI-based anisotropy specific to those regions.
| S-EPMC8854429 | biostudies-literature
Project description:Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.
| S-EPMC5677006 | biostudies-literature
Project description:Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible - determining where tracts "should" lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity. We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (-35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts "peak-to-peak" is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2?mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts. We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.
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Project description:We present a direct extension of probabilistic diffusion tractography to the case of multiple fibre orientations. Using automatic relevance determination, we are able to perform online selection of the number of fibre orientations supported by the data at each voxel, simplifying the problem of tracking in a multi-orientation field. We then apply the identical probabilistic algorithm to tractography in the multi- and single-fibre cases in a number of example systems which have previously been tracked successfully or unsuccessfully with single-fibre tractography. We show that multi-fibre tractography offers significant advantages in sensitivity when tracking non-dominant fibre populations, but does not dramatically change tractography results for the dominant pathways.
| S-EPMC7116582 | biostudies-literature
Project description:The structural connectivity network constructed using probabilistic diffusion tractography can be characterized by the network metrics. In this study, short-term test-retest reproducibility of structural networks and network metrics were evaluated on 30 subjects in terms of within- and between-subject coefficient of variance (CVws, CVbs), and intra class coefficient (ICC) using various connectivity thresholds. The short-term reproducibility under various connectivity thresholds were also investigated when subject groups have same or different sparsity. In summary, connectivity threshold of 0.01 can exclude around 80% of the edges with CVws?=?73.2?±?37.7%, CVbs?=?119.3?±?44.0% and ICC?=?0.62?±?0.19. The rest 20% edges have CVws?<?45%, CVbs?<?90%, ICC?=?0.75?±?0.12. The presence of 1% difference in the sparsity can cause additional within-subject variations on network metrics. In conclusion, applying connectivity thresholds on structural network to exclude spurious connections for the network analysis should be considered as necessities. Our findings suggest that a connectivity threshold over 0.01 can be applied without significant effect on the short-term when network metrics are evaluated at the same sparsity in subject group. When the sparsity is not the same, the procedure of integration over various connectivity thresholds can provide reliable estimation of network metrics.
| S-EPMC6070542 | biostudies-literature
Project description:Diffusion MRI (dMRI)-based tractography offers unique abilities to map whole-brain structural connections in human and animal brains. However, dMRI-based tractography indirectly measures white matter tracts, with suboptimal accuracy and reliability. Recently, sophisticated methods including constrained spherical deconvolution (CSD) and global tractography have been developed to improve tract reconstructions through modeling of more complex fiber orientations. Our study aimed to determine the accuracy of connectome reconstruction for three dMRI-based tractography approaches: diffusion tensor (DT)-based, CSD-based and global tractography. Therefore, we validated whole brain structural connectome reconstructions based on ten ultrahigh-resolution dMRI rat brain scans and 106 cortical regions, from which varying tractography parameters were compared against standardized neuronal tracer data. All tested tractography methods generated considerable numbers of false positive and false negative connections. There was a parameter range trade-off between sensitivity: 0.06-0.63 interhemispherically and 0.22-0.86 intrahemispherically; and specificity: 0.99-0.60 interhemispherically and 0.99-0.23 intrahemispherically. Furthermore, performance of all tractography methods decreased with increasing spatial distance between connected regions. Similar patterns and trade-offs were found, when we applied spherical deconvolution informed filtering of tractograms, streamline thresholding and group-based average network thresholding. Despite the potential of CSD-based and global tractography to handle complex fiber orientations at voxel level, reconstruction accuracy, especially for long-distance connections, remains a challenge. Hence, connectome reconstruction benefits from varying parameter settings and combination of tractography methods to account for anatomical variation of neuronal pathways.
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Project description:With the mapping of macroscale connectomes by means of in vivo diffusion-weighted MR Imaging (DWI) rapidly gaining in popularity, one of the necessary steps is the examination of metrics of connectivity strength derived from these reconstructions. In the field of human macroconnectomics the number of reconstructed fiber streamlines (NOS) is more and more used as a metric of cortico-cortical interareal connectivity strength, but the link between DWI NOS and in vivo animal tract-tracing measurements of anatomical connectivity strength remains poorly understood. In this technical report, we communicate on a comparison between DWI derived metrics and tract-tracing metrics of projection strength. Tract-tracing information on projection strength of interareal pathways was extracted from two commonly used macaque connectome datasets, including (1) the CoCoMac database of collated tract-tracing experiments of the macaque brain and (2) the high-resolution tract-tracing dataset of Markov and Kennedy and coworkers. NOS and density of reconstructed fiber pathways derived from DWI data acquired across 10 rhesus macaques was found to positively correlate to tract-tracing based measurements of connectivity strength across both the CoCoMac and Markov dataset (both P?<?0.001), suggesting DWI NOS to form a valid method of assessment of the projection strength of white matter pathways. Our findings provide confidence of in vivo DWI connectome reconstructions to represent fairly realistic estimates of the wiring strength of white matter projections. Our cross-modal comparison supports the notion of in vivo DWI to be a valid methodology for robust description and interpretation of brain wiring.
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Project description:Interest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data.
| S-EPMC4715247 | biostudies-literature
Project description:The insular cortex of macaques has a wide spectrum of anatomical connections whose distribution is related to its heterogeneous cytoarchitecture. Although there is evidence of a similar cytoarchitectural arrangement in humans, the anatomical connectivity of the insula in the human brain has not yet been investigated in vivo. In the present work, we used in vivo probabilistic white-matter tractography and Laplacian eigenmaps (LE) to study the variation of connectivity patterns across insular territories in humans. In each subject and hemisphere, we recovered a rostrocaudal trajectory of connectivity variation ranging from the anterior dorsal and ventral insula to the dorsal caudal part of the long insular gyri. LE suggested that regional transitions among tractography patterns in the insula occur more gradually than in other brain regions. In particular, the change in tractography patterns was more gradual in the insula than in the medial premotor region, where a sharp transition between different tractography patterns was found. The recovered trajectory of connectivity variation in the insula suggests a relation between connectivity and cytoarchitecture in humans resembling that previously found in macaques: tractography seeds from the anterior insula were mainly found in limbic and paralimbic regions and in anterior parts of the inferior frontal gyrus, while seeds from caudal insular territories mostly reached parietal and posterior temporal cortices. Regions in the putative dysgranular insula displayed more heterogeneous connectivity patterns, with regional differences related to the proximity with either putative granular or agranular regions.
| S-EPMC3443376 | biostudies-literature