Brain atlases and templates are at the heart of neuroimaging analyses, for which they facilitate multimodal registration, enable group comparisons and provide anatomical reference. However, as ...atlas-based approaches rely on correspondence mapping between images they perform poorly in the presence of structural pathology. Whilst several strategies exist to overcome this problem, their performance is often dependent on the type, size and homogeneity of any lesions present. We therefore propose a new solution, referred to as Virtual Brain Grafting (VBG), which is a fully-automated, open-source workflow to reliably parcellate magnetic resonance imaging (MRI) datasets in the presence of a broad spectrum of focal brain pathologies, including large, bilateral, intra- and extra-axial, heterogeneous lesions with and without mass effect.
The core of the VBG approach is the generation of a lesion-free T1-weighted image, which enables further image processing operations that would otherwise fail. Here we validated our solution based on Freesurfer recon-all parcellation in a group of 10 patients with heterogeneous gliomatous lesions, and a realistic synthetic cohort of glioma patients (n = 100) derived from healthy control data and patient data.
We demonstrate that VBG outperforms a non-VBG approach assessed qualitatively by expert neuroradiologists and Mann-Whitney U tests to compare corresponding parcellations (real patients U(6,6) = 33, z = 2.738, P < .010, synthetic-patients U(48,48) = 2076, z = 7.336, P < .001). Results were also quantitatively evaluated by comparing mean dice scores from the synthetic-patients using one-way ANOVA (unilateral VBG = 0.894, bilateral VBG = 0.903, and non-VBG = 0.617, P < .001). Additionally, we used linear regression to show the influence of lesion volume, lesion overlap with, and distance from the Freesurfer volumes of interest, on labeling accuracy.
VBG may benefit the neuroimaging community by enabling automated state-of-the-art MRI analyses in clinical populations using methods such as FreeSurfer, CAT12, SPM, Connectome Workbench, as well as structural and functional connectomics. To fully maximize its availability, VBG is provided as open software under a Mozilla 2.0 license (https://github.com/KUL-Radneuron/KUL_VBG).
Display omitted (A) shows T1 images from two patients with gliomatous lesions. VBG is a lesion replacement/filling workflow with one approach for unilateral lesions (uVBG) and one for bilateral lesion (bVBG). (B) shows the lesion filling and recon-all combination selected, (C) & (D) show the output, tissue segmentations (C) and whole brain parcellations (D). If VBG is not used (non-VBG) recon-all may quit without generating a parcellation (hard failure) shown on the lower left, or finish with some errors (soft failures) in the parcellations shown on the lower right. However, using either VBG method allows recon-all to complete where it had previously failed and also improves parcellation quality. (PAT = patient, VBG = virtual brain grafting, uVBG = unilateral VBG, bVBG = bilateral VBG)
Abstract Structural brain network topology can be altered in case of a brain tumor, due to both the tumor itself and its treatment. In this study, we explored the role of structural whole-brain and ...nodal network metrics and their association with cognitive functioning. Fifty WHO grade 2–3 adult glioma survivors (> 1-year post-therapy) and 50 matched healthy controls underwent a cognitive assessment, covering six cognitive domains. Raw cognitive assessment scores were transformed into w-scores, corrected for age and education. Furthermore, based on multi-shell diffusion-weighted MRI, whole-brain tractography was performed to create weighted graphs and to estimate whole-brain and nodal graph metrics. Hubs were defined based on nodal strength, betweenness centrality, clustering coefficient and shortest path length in healthy controls. Significant differences in these metrics between patients and controls were tested for the hub nodes (i.e. n = 12) and non-hub nodes (i.e. n = 30) in two mixed-design ANOVAs. Group differences in whole-brain graph measures were explored using Mann–Whitney U tests. Graph metrics that significantly differed were ultimately correlated with the cognitive domain-specific w-scores. Bonferroni correction was applied to correct for multiple testing. In survivors, the bilateral putamen were significantly less frequently observed as a hub ( p bonf < 0.001). These nodes’ assortativity values were positively correlated with attention ( r (90) > 0.573, p bonf < 0.001), and proxy IQ ( r (90) > 0.794, p bonf < 0.001). Attention and proxy IQ were significantly more often correlated with assortativity of hubs compared to non-hubs ( p bonf < 0.001). Finally, the whole-brain graph measures of clustering coefficient ( r = 0.685), global ( r = 0.570) and local efficiency ( r = 0.500) only correlated with proxy IQ ( p bonf < 0.001). This study demonstrated potential reorganization of hubs in glioma survivors. Assortativity of these hubs was specifically associated with cognitive functioning, which could be important to consider in future modeling of cognitive outcomes and risk classification in glioma survivors.
How verbal and nonverbal visuoperceptual input connects to semantic knowledge is a core question in visual and cognitive neuroscience, with significant clinical ramifications. In an event-related ...functional magnetic resonance imaging (fMRI) experiment we determined how cosine similarity between fMRI response patterns to concrete words and pictures reflects semantic clustering and semantic distances between the represented entities within a single category. Semantic clustering and semantic distances between 24 animate entities were derived from a concept-feature matrix based on feature generation by >1000 subjects. In the main fMRI study, 19 human subjects performed a property verification task with written words and pictures and a low-level control task. The univariate contrast between the semantic and the control task yielded extensive bilateral occipitotemporal activation from posterior cingulate to anteromedial temporal cortex. Entities belonging to a same semantic cluster elicited more similar fMRI activity patterns in left occipitotemporal cortex. When words and pictures were analyzed separately, the effect reached significance only for words. The semantic similarity effect for words was localized to left perirhinal cortex. According to a representational similarity analysis of left perirhinal responses, semantic distances between entities correlated inversely with cosine similarities between fMRI response patterns to written words. An independent replication study in 16 novel subjects confirmed these novel findings. Semantic similarity is reflected by similarity of functional topography at a fine-grained level in left perirhinal cortex. The word specificity excludes perceptually driven confounds as an explanation and is likely to be task dependent.
Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early ...region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.
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(Top) shows the FWT pipeline for both CSTs, AF, and motor CC bundles. (Left to right) show the required input structural parcellation maps and a priori atlases for FWT and the resulting virtual dissection include/exclude VOIs. FWT provides two approaches to virtual dissection: (1) is a bundle-specific approach where streamlines are only seeded for the bundle of interest, (2) is a whole brain tractography followed by streamlines segmentation, (top right) shows output tractograms. (Middle) Group-averaged T1 and fODF images are generated from the HCP test-retest data, and FWT is applied to generate the HCP- atlas using the bundle-specific approach (1*). FWT's whole brain tracking and segmentation approach (2*) was applied to the HCP and MASSIVE dataset (right and left) and conducted model-based, and pair-wise similarity analyses and generated voxel-wise cumulative maps per bundle. FWT = Fun With Tracts, FS = FreeSurfer, MSBP = MultiScaleBrainParcellator, PD25 = NIST Parkinson's histological, JHU = John's Hopkins university, Juelich = Juelich university histological atlas, AC/PC = anterior commissure/posterior commissure) UKBB = UK Biobank, SUIT (spatially unbiased cerebellar atlas template), dMRI = diffusion magnetic resonance imaging, CSD = constrained spherical deconvolution, fODF = fiber orientation distribution function, CST = corticospinal tract, AF = arcuate fasciculus, CC = corpus callosum, HCP = human connectome project, MASSIVE = Multiple acquisitions for standardization of structural imaging validation and evaluation.
EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset ...zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular ‘bridge’ between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response’s variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.
This review provides a comprehensive overview of brain imaging studies of the brain-gut interaction in functional gastrointestinal disorders (FGIDs). Functional neuroimaging studies during gut ...stimulation have shown enhanced brain responses in regions related to sensory processing of the homeostatic condition of the gut (homeostatic afferent) and responses to salience stimuli (salience network), as well as increased and decreased brain activity in the emotional response areas and reduced activation in areas associated with the top-down modulation of visceral afferent signals. Altered central regulation of the endocrine and autonomic nervous responses, the key mediators of the brain-gut axis, has been demonstrated. Studies using resting-state functional magnetic resonance imaging reported abnormal local and global connectivity in the areas related to pain processing and the default mode network (a physiological baseline of brain activity at rest associated with self-awareness and memory) in FGIDs. Structural imaging with brain morphometry and diffusion imaging demonstrated altered gray- and white-matter structures in areas that also showed changes in functional imaging studies, although this requires replication. Molecular imaging by magnetic resonance spectroscopy and positron emission tomography in FGIDs remains relatively sparse. Progress using analytical methods such as machine learning algorithms may shift neuroimaging studies from brain mapping to predicting clinical outcomes. Because several factors contribute to the pathophysiology of FGIDs and because its population is quite heterogeneous, a new model is needed in future studies to assess the importance of the factors and brain functions that are responsible for an optimal homeostatic state.
•GABAAR availability was higher in older as compared to young adults.•GABAAR activity and GABA+ levels were similar across age groups.•GABAAR availability, GABAAR activity and GABA+ levels were not ...correlated.
Healthy aging is associated with mechanistic changes in gamma-aminobutyric acid (GABA), the most abundant inhibitory neurotransmitter in the human brain. While previous work mainly focused on magnetic resonance spectroscopy (MRS)-based GABA+ levels and transcranial magnetic stimulation (TMS)-based GABAA receptor (GABAAR) activity in the primary sensorimotor (SM1) cortex, the aim of the current study was to identify age-related differences in positron emission tomography (PET)-based GABAAR availability and its relationship with GABA+ levels (i.e. GABA with the contribution of macromolecules) and GABAAR activity. For this purpose, fifteen young (aged 20–28 years) and fifteen older (aged 65–80 years) participants were recruited. PET and MRS images were acquired using simultaneous time-of-flight PET/MR to evaluate age-related differences in GABAAR availability (distribution volume ratio with pons as reference region) and GABA+ levels. TMS was applied to identify age-related differences in GABAAR activity by measuring short-interval intracortical inhibition (SICI). Whereas GABAAR availability was significantly higher in the SM cortex of older as compared to young adults (18.5%), there were neither age-related differences in GABA+ levels nor SICI. A correlation analysis revealed no significant associations between GABAAR availability, GABAAR activity and GABA+ levels. Although the exact mechanisms need to be further elucidated, it is possible that a higher GABAAR availability in older adults is a compensatory mechanism to ensure optimal inhibitory functionality during the aging process.
The examination of semantic cognition has traditionally identified word concreteness as well as valence as two of the principal dimensions in the representation of conceptual knowledge. More ...recently, corpus-based vector space models as well as graph-theoretical analysis of large-scale task-related behavioural responses have revolutionized our insight into how the meaning of words is structured. In this fMRI study, we apply representational similarity analysis to investigate the conceptual representation of abstract words. Brain activity patterns were related to a cued-association based graph as well as to a vector-based co-occurrence model of word meaning. Twenty-six subjects (19 females and 7 males) performed an overt repetition task during fMRI. First, we performed a searchlight classification procedure to identify regions where activity is discriminable between abstract and concrete words. These regions were left inferior frontal gyrus, the upper and lower bank of the superior temporal sulcus bilaterally, posterior middle temporal gyrus and left fusiform gyrus. Representational Similarity Analysis demonstrated that for abstract words, the similarity of activity patterns in the cortex surrounding the superior temporal sulcus bilaterally and in the left anterior superior temporal gyrus reflects the similarity in word meaning. These effects were strongest for semantic similarity derived from the cued association-based graph and for affective similarity derived from either of the two models. The latter effect was mainly driven by positive valence words. This research highlights the close neurobiological link between the information structure of abstract and affective word content and the similarity in activity pattern in the lateral and anterior temporal language system.
•26 subjects performed an overt repetition task on visual and auditory words.•SVM classification discriminated between concrete vs. abstract words in IFG, fusiform gyrus, superior temporal cortex.•Neural similarities in the superior temporal gyrus and semantic similarities correlated significantly for abstract words.•We highlight the neurobiological link between abstract and affective word content and the temporal language system.
Based on lesion mapping studies, the inferior parietal lobule and temporoparietal junction are considered the critical parietal regions for spatial-attentional deficits. Lesion evidence for a key ...role of the intraparietal sulcus, a region featuring prominently in non-human primate studies and human functional imaging studies of the intact brain, is still lacking, probably due to the exceptional nature of isolated intraparietal sulcus lesions. We combined behavioural testing and functional imaging in two patients with a focal intraparietal sulcus lesion sparing the inferior parietal lobule and temporoparietal junction to examine the critical contribution of the intraparietal sulcus to spatial attention. Case H.H. had a focal ischaemic lesion (1.8 cm3) that was confined to the posterior segment of the left intraparietal sulcus, whereas Case N.V. had a partially reversible lesion of the middle segment of the right intraparietal sulcus extending into the superior parietal lobule (13.8 cm3). The performance of these cases was contrasted with five cases with a classical inferior parietal lesion, as well as with a group of 31 age-matched controls. In the behavioural study, the patients performed an orientation discrimination task on a peripheral target (eccentricity 7.6°) that was preceded by a central spatial cue. We manipulated both the cue validity (17% trials with an invalid spatial cue) and the presence of a competing distracter in the visual field contralateral to the target (17% double stimulation trials). The ability of the patients with an intraparietal sulcus lesion to reorient their spatial focus of attention and to select between competing stimuli was impaired for contralesional targets compared with controls, similarly to what we saw in the inferior parietal group. Furthermore, we could observe that the deficit in Case N.V. resolved with regression of the lesion. To further evaluate the correspondence between spatial-attentional deficits and the intraparietal sulcus lesions, we ascertained the functional integrity of the inferior parietal lobule and temporoparietal junction in Case H.H. using event-related functional magnetic resonance imaging with the same task as in the behavioural study. The intraparietal sulcus lesion of this patient did not affect the task-related activation of the inferior parietal lobule or temporoparietal junction. Additionally, a resting-state functional magnetic resonance imaging study in Case H.H. and 62 controls revealed that the lesion in Case H.H. did not affect the topology of the ventral attention network nor the strength of its main inter- and intrahemispheric connections. Our findings demonstrate that the human superior parietal cortex critically contributes to spatially selective attention.
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