Michaël Bernier

Structural network underlying visuospatial imagery in humans

INTRODUCTION Several neuroimaging studies have shown that visuospatial imagery is associated with a multitude of activation nodes spanning occipital, parietal, temporal and frontal brain areas. However, the anatomical connectivity profile linking these areas is not well understood. Specifically, it is unknown whether cortical areas activated during visuospatial imagery are directly connected to one another, or whether few act as hubs which facilitate indirect connections between distant sites. Addressing this is important since mental imagery tasks are commonly used in clinical settings to assess complex cognitive functions such as spatial orientation. METHODS We recorded functional magnetic resonance imaging (fMRI) data while participants (N = 18) performed a visuospatial imagery task. In the same subjects, we acquired diffusion MRI (dMRI) and used state-of-the-art tractography robust to fiber crossings to reconstruct the white matter tracts linking the fMRI activation sites. For each pair of these sites, we then computed the fraction of subjects showing a connection between them. RESULTS Robust fMRI activation was observed in cortical areas spanning the dorsal (extrastriate, parietal and prefrontal areas) and ventral (temporal and lingual areas) pathways, as well as moderate deactivation in striate visual cortex. In over 80% of subjects, striate cortex showed anatomical connectivity with extrastriate (medial occipital) and lingual (posterior cingulate cortex-PCC) sites with the latter showing divergent connections to ventral (parahippocampus) and dorsal (BA7) activation areas. CONCLUSION Our results demonstrate that posterior cingulate cortex is not only activated by visuospatial imagery, but also serves as an anatomical hub linking activity in occipital, parietal and temporal areas. This finding adds to the growing body of evidence pointing to PCC as a connector hub which may facilitate integration across widespread cortical areas.

3D interactive tractography-informed resting-state fMRI connectivity.

In the past decade, the fusion between diffusion magnetic resonance imaging (dMRI) and functional magnetic resonance imaging (fMRI) has opened the way for exploring structure-function relationships in vivo. As it stands, the common approach usually consists of analysing fMRI and dMRI datasets separately or using one to inform the other, such as using fMRI activation sites to reconstruct dMRI streamlines that interconnect them. Moreover, given the large inter-individual variability of the healthy human brain, it is possible that valuable information is lost when a fixed set of dMRI/fMRI analysis parameters such as threshold values are assumed constant across subjects. By allowing one to modify such parameters while viewing the results in real-time, one can begin to fully explore the sensitivity of structure-function relations and how they differ across brain areas and individuals. This is especially important when interpreting how structure-function relationships are altered in patients with neurological disorders, such as the presence of a tumor. In this study, we present and validate a novel approach to achieve this: First, we present an interactive method to generate and visualize tractography-driven resting-state functional connectivity, which reduces the bias introduced by seed size, shape and position. Next, we demonstrate that structural and functional reconstruction parameters explain a significant portion of intra- and inter-subject variability. Finally, we demonstrate how our proposed approach can be used in a neurosurgical planning context. We believe this approach will promote the exploration of structure-function relationships in a subject-specific aspect and will open new opportunities for connectomics.

Spatial distribution of resting-state BOLD regional homogeneity as a predictor of brain glucose uptake: A study in healthy aging

Abstract Positron emission tomography using [18F]‐fluorodeoxyglucose (PET‐FDG) is the primary imaging modality used to measure glucose metabolism in the brain (CMRGlu). CMRGlu has been used as a biomarker of brain aging and neurodegenerative diseases, but the complexity and invasive nature of PET often limits its use in research. There is therefore great interest in developing non‐invasive metrics for estimating brain CMRGlu. We therefore investigated resting state fMRI metrics such as regional homogeneity (ReHo), amplitude of low‐frequency fluctuations (ALFF) and regional global connectivity (Closeness) with multiple analytical approaches to determine their relationship to CMRGlu. We investigated this relation in two distinct cognitively healthy populations separated by age (27 young adults and 35 older adults). Overall, we found that both regionally and across participants, ReHo strongly correlated with CMRGlu in healthy young and older adults. Moreover, ReHo demonstrated the same age‐related differences as CMRGlu throughout all cortical regions, particularly in the default network and frontal areas. HighlightsPET‐FDG accurately represents glucose metabolism (CMRGlu), but remains complex and invasive;Finding a quantitative relationship between CMRGlu and an fMRI metric has been elusive;We used a cognitively healthy aging dataset to compare fMRI to CMRGlu in the grey matter;fMRI local synchrony (ReHo) correlated well to CMRGlu in both young and older groups;ReHo could be used as a semi‐quantitative proxy of CMRGlu and as a biomarker of aging.

Practices of Return-to-Work Coordinators Working in Large Organizations.

Purpose Although the role of return-to-work coordinators (RTW coordinators) is associated with reducing long-term disabilities, little has been written about their practices. The objective of this study was to clearly identify their tasks and activities and the stakeholders with whom they collaborate. Methods A cross-sectional survey was conducted using a web-based self-administered questionnaire. Participant inclusion criteria were as follows: (1) working for a large organization with 500 or more employees; (2) being responsible for managing disabilities and coordinating the return-to-work process; and (3) having been involved in coordinating the return to work of at least one person in the past year. Results 195 RTW coordinators completed the questionnaire. The three tasks or activities rated as most important were applying laws, policies, and regulations related to work absences and return to work; contacting the absent worker; and planning the return to work. A nursing or occupational health and safety training background significantly influenced the RTW coordinators’ practices. In addition, RTW coordinators collaborated mainly with workers and their supervisors. Conclusion Despite a wide variety of contexts and diverging definitions of competencies, a set of common RTW coordination practices appears to exist across industrialized countries. RTW coordinators with a training background in the health field seem better able to assimilate the various dimensions of work disability. Moreover, concerted action was found to be minimal and a far cry from recommendations. The practices defined could serve as a benchmark for describing RTW coordinators’ responsibilities in greater detail and allow for cross-organization and cross-country comparisons.

Stimulus-evoked changes in cerebral vessel diameter: A study in healthy humans

The high metabolic demand of neuronal tissue, coupled with its relatively low energy storage capacity, requires that increases in neuronal activation are quickly matched with increased blood flow to ensure efficient supply of oxygen and nutrients to the tissue. For this to occur, dilation of nearby arterioles must be coordinated with the dilation of larger upstream feeding arteries. As it stands, the exact spatial extent of such dilation in humans is unknown. Using non-invasive time-of-flight magnetic resonance angiography in healthy participants, we developed an automatic methodology for reconstructing cerebral arterial vessels and quantifying their diameter on a voxel-by-voxel basis. Specifically, we isolated the posterior cerebral artery (PCA) supplying each occipital lobe and quantified its vasodilation induced by visual stimulation. Stimulus-induced changes were strongest (∼30%) near primary visual cortex and progressively decreased in a non-linear fashion as a function of distance. Surprisingly, weak – albeit significant – changes (∼2%) were observed ∼70 mm from the visual cortex. This demonstrates that visual stimulation modulates vascular tone along the bulk of the PCA segment, and thus may have important implications for our understanding of functional hyperemia in healthy and diseased states.

Semi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves

At rest, healthy human brain activity is characterized by large electroencephalography (EEG) fluctuations in the 8-13 Hz range, commonly referred to as the alpha band. Although it is well known that EEG alpha activity varies across individuals, few studies have investigated how this may be related to underlying morphological variations in brain structure. Specifically, it is generally believed that the lateral geniculate nucleus (LGN) and its efferent fibres (optic radiation, OR) play a key role in alpha activity, yet it is unclear whether their shape or size variations contribute to its inter-subject variability. Given the widespread use of EEG alpha in basic and clinical research, addressing this is important, though difficult given the problems associated with reliably segmenting the LGN and OR. For this, we employed a multi-modal approach and combined diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI) and EEG in 20 healthy subjects to measure structure and function, respectively. For the former, we developed a new, semi-automated approach for segmenting the OR and LGN, from which we extracted several structural metrics such as volume, position and diffusivity. Although these measures corresponded well with known morphology based on previous post-mortem studies, we nonetheless found that their inter-subject variability was not significantly correlated to alpha power or peak frequency (p >0.05). Our results therefore suggest that alpha variability may be mediated by an alternative structural source and our proposed methodology may in general help in better understanding the influence of anatomy on function such as measured by EEG or fMRI.

Graph cut-based method for segmenting the left ventricle from MRI or echocardiographic images

In this paper, we present a fast and interactive graph cut method for 3D segmentation of the endocardial wall of the left ventricle (LV) adapted to work on two of the most widely used modalities: magnetic resonance imaging (MRI) and echocardiography. Our method accounts for the fundamentally different nature of both modalities: 3D echocardiographic images have a low contrast, a poor signal-to-noise ratio and frequent signal drop, while MR images are more detailed but also cluttered and contain highly anisotropic voxels. The main characteristic of our method is to work in a 3D Bezier coordinate system instead of the original Euclidean space. This comes with several advantages, including an implicit shape prior and a result guarantied not to have any holes in it. The proposed method is made of 4 steps. First, a 3D sampling of the LV cavity is made based on a Bezier coordinate system. This allows to warp the input 3D image to a Bezier space in which a plane corresponds to an anatomically plausible 3D Euclidean bullet shape. Second, a 3D graph is built and an energy term (which is based on the image gradient and a 3D probability map) is assigned to each edge of the graph, some of which being given an infinite energy to ensure the resulting 3D structure passes through key anatomical points. Third, a max-flow min-cut procedure is executed on the energy graph to delineate the endocardial surface. And fourth, the resulting surface is projected back to the Euclidean space where a post-processing convex hull algorithm is applied on every short axis slice to remove local concavities. Results obtained on two datasets reveal that our method takes between 2 and 5s to segment a 3D volume, it has better results overall than most state-of-the-art methods on the CETUS echocardiographic dataset and is statistically as good as a human operator on MR images.

On the Origin of Individual Functional Connectivity Variability: The Role of White Matter Architecture

Fingerprint patterns derived from functional connectivity (FC) can be used to identify subjects across groups and sessions, indicating that the topology of the brain substantially differs between individuals. However, the source of FC variability inferred from resting-state functional magnetic resonance imaging remains unclear. One possibility is that these variations are related to individual differences in white matter structural connectivity (SC). However, directly comparing FC with SC is challenging given the many potential biases associated with quantifying their respective strengths. In an attempt to circumvent this, we employed a recently proposed test-retest approach that better quantifies inter-subject variability by first correcting for intra-subject nuisance variability (i.e., head motion, physiological differences in brain state, etc.) that can artificially influence FC and SC measures. Therefore, rather than directly comparing the strength of FC with SC, we asked whether brain regions with, for example, low inter-subject FC variability also exhibited low SC variability. From this, we report two main findings: First, at the whole-brain level, SC variability was significantly lower than FC variability, indicating that an individuals structural connectome is far more similar to another relative to their functional counterpart even after correcting for noise. Second, although FC and SC variability were mutually low in some brain areas (e.g., primary somatosensory cortex) and high in others (e.g., memory and language areas), the two were not significantly correlated across all cortical and sub-cortical regions. Taken together, these results indicate that even after correcting for factors that may differently affect FC and SC, the two, nonetheless, remain largely independent of one another. Further work is needed to understand the role that direct anatomical pathways play in supporting vascular-based measures of FC and to what extent these measures are dictated by anatomical connectivity.

Increased BOLD activation in the left parahippocampal cortex after 1 year of medical school: an association with cumulative verbal memory learning.

Although several studies have shown left–right hippocampus asymmetry during learning, it is unclear whether such asymmetry also exists for the parahippocampal cortex, a structure within the limbic system that is also involved in memory and learning. Using a common mental navigation task known to activate the bilateral parahippocampal cortex, this study aimed at determining how BOLD activation in these two areas changes after 1 year of medical school, a program characterized by intensive verbal learning. Fifteen first-year medical students participated in this study and underwent two sessions of functional MRI, at a 1-year interval. In the first session, we observed marginal differences between left and right parahippocampal cortex activity. However, 1 year later, left parahippocampal activation significantly increased (+4.7%), whereas the right remained stable. These results bring new information as to how intensive learning can modify regional metabolism in the human brain and how the left parahippocampal region is particularly important for cumulative verbal memory.

The morphology of the human cerebrovascular system

While several methodologies exist for quantifying gray and white matter properties in humans, relatively little is known regarding the spatial organization and the intersubject variability of cerebral vessels. To resolve this, we developed a fast, open‐source processing algorithm using advanced vessel segmentation schemes and iterative nonlinear registration to isolate, extract, and quantify cerebral vessels in susceptibility weighting imaging (SWI) and time‐of‐flight angiography (TOF‐MRA) datasets acquired in a large cohort (n = 42) of healthy individuals. From this, whole‐brain venous and arterial probabilistic maps were generated along with the computation of regional densities and diameters within regions based on popular anatomical and functional atlases. The results show that cerebral vasculature is highly heterogeneous, displaying disproportionally large vessel densities in brain areas such as the anterior and posterior cingulate, cuneus, precuneus, parahippocampus, insula, and temporal gyri. On average, venous densities were slightly higher and less variable across subjects than arterial. Moreover, regional variations in both venous and arterial density were significantly correlated to cortical thickness (R = 0.42). This publicly available new atlas of the human cerebrovascular system provides a first step toward quantifying morphological changes in the diseased brain and serving as a potential regression tool in fMRI analysis.