Oury Monchi

Habib Benali

Julien Doyon

Antonio P. Strafella

Recent Advances in Neuroimaging Methods

A large-scale brain network can be defined as a set of segregated and integrated
regions, that is, distant regions that share strong anatomical connections
and functional interactions. Data-driven investigation of such networks has
recently received a great deal of attention in blood-oxygen-level-dependent
(BOLD) functional magnetic resonance imaging (fMRI). We here review the
rationale for such an investigation, the methods used, the results obtained,
and also discuss some issues that have to be faced for an efficient exploration.

V. Perlbarg

G. Marrelec

Contribution of Exploratory Methods to the Investigation  of Extended Large-Scale Brain Networks in Functional MRI: Methodologies, Results, and Challenges

Diffusion tensor imaging (DTI) is considered to be a promising tool for revealing the anatomical basis of functional networks. In this study, we investigate the potential of DTI to provide the anatomical basis of paths that are used in studies of effective connectivity, using structural equation modeling. We have taken regions of interest from eight previously published studies, and examined the connectivity as defined by DTI-based fiber tractography between these regions. The resulting fiber tracts were then compared with the paths proposed in the original studies. For a substantial number of connections, we found fiber tracts that corresponded to the proposed paths. More importantly, we have also identified a number of cases in which tractography suggested direct connections which were not included in the original analyses. We therefore conclude that DTI-based fiber tractography can be a valuable tool to study the anatomical basis of functional networks.

Hubert M. J. Fonteijn

David G. Norris

Frans A. J. Verstraten

Exploring the Anatomical Basis of Effective Connectivity Models with DTI-Based Fiber Tractography

This paper exploits the idea that each individual brain region has a specific connection profile to create parcellations of the cortical mantle using MR diffusion imaging. The parcellation is performed in two steps. First, the cortical mantle is split at a macroscopic level into 36 large gyri using a sulcus recognition system. Then, for each voxel of the cortex, a connection profile is computed using a probabilistic tractography framework. The tractography is performed from <mml:math id="E2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>q</mml:mi></mml:math>-ball fields using regularized particle trajectories. Fiber ODF are inferred from the <mml:math id="E3" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>q</mml:mi></mml:math>-balls using a sharpening process focusing the weight around the <mml:math id="E4" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>q</mml:mi></mml:math>-ball local maxima. A sophisticated mask of propagation computed from a T1-weighted image perfectly aligned with the diffusion data prevents the particles from crossing the cortical folds. During propagation, the particles father child particles in order to improve the sampling of the long fascicles. For each voxel, intersection of the particle trajectories with the gyri lead to a connectivity profile made up of only 36 connection strengths. These profiles are clustered on a gyrus by gyrus basis using a <mml:math id="E5" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>K</mml:mi></mml:math>-means approach including spatial regularization. The reproducibility of the results is studied for three subjects using spatial normalization.

Muriel Perrin

Yann Cointepas

Arnaud Cachia

Cyril Poupon

Bertrand Thirion

Denis Rivière

Pascal Cathier

Vincent El Kouby

André Constantinesco

Denis Le Bihan

Jean-François Mangin

Connectivity-Based Parcellation of the Cortical Mantle Using <svg style="vertical-align:-3.50804pt" height="12.1125" version="1.1" viewBox="0 0 8.4750004 12.1125" width="8.4750004" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,7.675)"><path id="x1D45E" d="M474 429q-19 -69 -47 -222l-65 -347q-8 -49 0 -60t49 -16l26 -3l-4 -26l-246 -12l4 25l17 3q37 6 50 20.5t23 60.5l67 321h-2q-65 -79 -150 -138q-69 -47 -104 -47q-28 0 -48.5 32t-20.5 81q0 78 35 148t90 117q67 57 161 77q23 5 58 5q43 0 90 -15zM387 387
q-30 16 -75 16q-58 0 -92 -27q-49 -39 -78.5 -112t-29.5 -136q0 -34 8.5 -52.5t21.5 -18.5q40 0 109.5 63.5t103.5 115.5q16 53 32 151z"/></g></svg>-Ball Diffusion Imaging

Previous studies have suggested that during selective activation of a subset of the zones comprising a columnar system in visual cortex, perfusion increases uniformly in all columns of the system, while increases in oxidative metabolism occur predominantly in the activated columns. This could lead to disproportionately large blood oxygenation level-dependent (BOLD) signal increases for a given flow increase during monocular (relative to binocular) stimulation, due to contributions from columns which undergo large increases in perfusion with little or no change in oxidative metabolism.  In the present study, we sought to test this hypothesis by measuring BOLD-perfusion coupling ratios in spatially averaged signals over V1 during monocular and binocular visual stimulation. It was found that, although withholding input to one eye resulted in statistically significant decreases in BOLD and perfusion signals in primary visual cortex, the ratio between BOLD and perfusion increases did not change significantly. These results do not support a gross mismatch between spatial patterns of flow and metabolism response during monocular stimulation.

Claudine Gauthier

Richard D. Hoge

BOLD-Perfusion Coupling during Monocular and Binocular Stimulation

Early functional neuroimaging studies of tasks evaluating executive processes, such as the Wisconsin card sorting task (WCST), only assessed trials in blocks that may contain a large amount of different cognitive processes. More recently, we showed using event-related fMRI that the dorsolateral prefrontal cortex (DL-PFC) significantly increased activity during feedback but not matching periods of the WCST, consistent with its proposed role in the monitoring of information in working memory. Repetitive transcranial magnetic stimulation (rTMS) is a method that allows to disrupt processing within a given cortical region and to affect task performance for which this region is significantly solicited. Here we applied rTMS to test the hypothesis that the DL-PFC stimulation influences monitoring of working memory without interfering with other executive functions. We applied rTMS to the right DL-PFC and the vertex (control site) in different time points of the WCST. When rTMS was applied to the DL-PFC specifically during the period when subjects were receiving feedback regarding their previous response, WCST performance deteriorated, while rTMS did not affect performance during matching either when maintaining set or during set-shifting. This selective impairment of the DL-PFC is consistent with its proposed role in monitoring of events in working memory.

Ji Hyun Ko

Alain Ptito

Michael Petrides

Repetitive Transcranial Magnetic Stimulation of Dorsolateral Prefrontal Cortex Affects Performance of the Wisconsin Card Sorting Task during Provision of Feedback

White matter fiber clustering aims to get insight about anatomical structures in order to generate atlases, perform clear visualizations, and compute statistics across subjects, all important and current neuroimaging problems. In this work, we present a diffusion maps clustering method applied to diffusion MRI in order to segment complex white matter fiber bundles. It is well known that diffusion tensor imaging (DTI) is restricted in complex fiber regions with crossings and this is why recent high-angular resolution diffusion imaging (HARDI) such as Q-Ball imaging (QBI) has been introduced to overcome these limitations. QBI reconstructs the diffusion orientation distribution function (ODF), a spherical function that has its maxima agreeing with the underlying fiber populations. In this paper, we use a spherical harmonic ODF representation as input to the diffusion maps clustering method. We first show the advantage of using diffusion maps clustering over classical methods such as N-Cuts and Laplacian eigenmaps. In particular, our ODF diffusion maps requires a smaller number of hypothesis from the input data, reduces the number of artifacts in the segmentation, and automatically exhibits the number of clusters segmenting the Q-Ball image by using an adaptive scale-space parameter. We also show that our ODF diffusion maps clustering can reproduce published results using the diffusion tensor (DT) clustering with N-Cuts on simple synthetic images without crossings. On more complex data with crossings, we show that our ODF-based method succeeds to separate fiber bundles and crossing regions whereas the DT-based methods generate artifacts and exhibit wrong number of clusters. Finally, we show results on a real-brain dataset where we segment well-known fiber bundles.

Demian Wassermann

Maxime Descoteaux

Rachid Deriche

Diffusion Maps Clustering for Magnetic Resonance Q-Ball Imaging Segmentation

Previous studies in nonhuman primates and cats have shown that the pulvinar receives input from various cortical and subcortical areas involved in vision. Although the contribution of the pulvinar to human vision remains to be established, anatomical tracer and electrophysiological animal studies on cortico-pulvinar circuits suggest an important role of this structure in visual spatial attention, visual integration, and higher-order visual processing. Because methodological constraints limit investigations of the human pulvinar's function, its role could, up to now, only be inferred from animal studies. In the present study, we used an innovative imaging technique, Diffusion Tensor Imaging (DTI) tractography, to determine cortical and subcortical connections of the human pulvinar. We were able to reconstruct pulvinar fiber tracts and compare variability across subjects in vivo. Here we demonstrate that the human pulvinar is interconnected with subcortical structures (superior colliculus, thalamus, and caudate nucleus) as well as with cortical regions (primary visual areas (area 17), secondary visual areas (area 18, 19), visual inferotemporal areas (area 20), posterior parietal association areas (area 7), frontal eye fields and prefrontal areas). These results are consistent with the connectivity reported in animal anatomical studies.

Sandra E. Leh

M. Mallar Chakravarty

The Connectivity of the Human Pulvinar: A Diffusion Tensor Imaging Tractography Study

Noninvasive techniques such as functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) have provided insight into understanding how neural connections are altered in consequence to cerebrovascular injury. The first part of this review will briefly survey some of the methodological issues and limitations related to noninvasive poststroke motor recovery studies. The second section will investigate some of the different neural mechanisms that underlie neurorehabilitation in stroke patients. The third part will explore our current understanding of motor memory processing, describe the neural structures that subserve motor memory consolidation, and discuss the current literature related to memory reconsolidation in healthy adults. Lastly, this paper will suggest the potential therapeutic applications of integrating noninvasive tools with memory consolidation and reconsolidation theories to enhance motor recovery. The overall objective of this work is to demonstrate how noninvasive technologies have been utilized in the multidisciplinary field of clinical behavioral neuroscience and to highlight their potential to be employed as clinical tools to promote individualized motor recovery in stroke patients.

Daniel Maxwell Bernad

The Role of Noninvasive Techniques in Stroke Therapy

Using geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method optimises a global criterion, and hence is less sensitive to local perturbations such as noise or partial volume effects, and (ii) the method is fast, allowing to infer on a large number of connexions in a reasonable computational time. Here, we propose an improved fast marching algorithm to infer on geodesic paths. Specifically, this procedure is designed to achieve accurate front propagation in an anisotropic elliptic medium, such as DTI data. We evaluate the numerical performance of this approach on simulated datasets, as well as its robustness to local perturbation induced by fiber crossing. On real data, we demonstrate the feasibility of extracting geodesics to connect an extended set of brain regions.

S. Jbabdi

P. Bellec

R. Toro

J. Daunizeau

M. P&#xE9;l&#xE9;grini-Issac

H. Benali

Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography

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International Journal of Biomedical Imaging aims to promote research and development of biomedical imaging by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field.

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International Journal of Biomedical Imaging

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