Inter-subject Connectivity-Based Parcellation of a Patch of Cerebral Cortex

Roca, Pauline; Tucholka, Alan; Rivière, Denis; Guevara, Pamela; Poupon, Cyril; Mangin, Jean‐François

doi:10.1007/978-3-642-15745-5_43

Cited by 21 publications

(32 citation statements)

References 14 publications

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“…It is not currently possible to perform connectivity-based parcellation on the whole brain at once, since the precision of the clustering relies on a description of connected regions which depend on the input patch. In this paper, the post central gyrus was taken as an example of patch in order to compare our results with the initial approach [7]. The general methodology is described in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

“…A spatial smoothing was then applied on the matrix using the mesh geometry by solving the heat equation, while preserving the amount of connections. This new step replaces the Gaussian smoothing used by [7] to increase the stability of the method. To assess the impact of smoothing on parcellation, we computed the connectivity matrix with different smoothing (0, 3 or 5mm).…”

Section: Individual Connectivity Profilesmentioning

confidence: 98%

“…A mask on the complete cortical surface is generated with the following constraints: a sufficient overlap across subjects and a high connections density. Compared to [7], parameters have been manually optimized to ensure robustness and low sensitivity to the variability of initial data: cortex mesh structure, fibers tracking data, number of subjects.…”

Section: Joint Patch Connectivity Profilementioning

confidence: 99%

“…This work is the continuity of the works of Roca [7], which main originality relied on the definition of homogeneous feature regions based directly on connectivity information rather than on predefined anatomical regions, obtained by applying the watershed algorithm to an average connectivity profile information. The main contribution of the current paper was to implement a validation procedure, leading to reveal a reproducible pattern in some cortical regions.…”

Section: Introductionmentioning

confidence: 99%

“…A new set of high quality data has been used to perform cross-validations, so as to assess the stability of the results. The processing pipeline has also been revised, improved and robustified to push the approach at the level of all gyri when [7] was applied on a single gyrus. The reworked processing chain now brings the possibility to process large and various datasets (many subjects and large connectivity data).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Validation of consistent inter-subject connectivity-based parcellation

Lefranc¹,

Roca²,

Perrot³

et al. 2014

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)

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Splitting the cortical surface into regions with homogeneous dMRI-based connectivity profiles is a promising but challenging topic. This paper extends the inter-subject connectivity-based cortex parcellation framework proposed by Roca [1]. In a first step, we implement the state-of-the-art algorithm with tuned parameters and, then propose a refined algorithm validated on the large high quality ARCHI database. This algorithm consists in clustering and subdividing each gyrus, in a reasonable time. Cross-validation shows that the resulting patterns are reproducible across groups. The stability is illustrated for the post-central gyrus of three different groups of subjects. Finally, the method has successfully been made robust to initial conditions: tracking type, cortical mesh characteristics and boundaries of gyri.

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Section: Methodsmentioning

confidence: 99%

Section: Individual Connectivity Profilesmentioning

confidence: 98%

Section: Joint Patch Connectivity Profilementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Validation of consistent inter-subject connectivity-based parcellation

Lefranc¹,

Roca²,

Perrot³

et al. 2014

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)

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A hierarchical method for whole‐brain connectivity‐based parcellation

Moreno-Dominguez

Anwander

Knösche

2014

Human Brain Mapping

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In modern neuroscience there is general agreement that brain function relies on networks and that connectivity is therefore of paramount importance for brain function. Accordingly, the delineation of functional brain areas on the basis of diffusion magnetic resonance imaging (dMRI) and tractography may lead to highly relevant brain maps. Existing methods typically aim to find a predefined number of areas and/or are limited to small regions of grey matter. However, it is in general not likely that a single parcellation dividing the brain into a finite number of areas is an adequate representation of the function-anatomical organization of the brain. In this work, we propose hierarchical clustering as a solution to overcome these limitations and achieve whole-brain parcellation. We demonstrate that this method encodes the information of the underlying structure at all granularity levels in a hierarchical tree or dendrogram. We develop an optimal tree building and processing pipeline that reduces the complexity of the tree with minimal information loss. We show how these trees can be used to compare the similarity structure of different subjects or recordings and how to extract parcellations from them. Our novel approach yields a more exhaustive representation of the real underlying structure and successfully tackles the challenge of whole-brain parcellation.

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Sensorimotor network alterations in children and youth with prenatal alcohol exposure

Long

Little

Beaulieu

et al. 2018

Human Brain Mapping

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Children with prenatal alcohol exposure (PAE) often have impaired sensorimotor function. While altered brain structure has been noted in sensorimotor areas, the functional brain alterations remain unclear. This study aims to investigate sensorimotor brain networks in children and youth with PAE using resting-state functional magnetic resonance imaging (rs-fMRI). A parcellation-based network analysis was performed to identify brain networks related to hand/lower limb and face/upper limb function in 59 children and youth with PAE and 50 typically developing controls. Participants with PAE and controls had similar organization of the hand and face areas within the primary sensorimotor cortex, but participants with PAE had altered functional connectivity (FC) between the sensorimotor regions and the rest of the brain. The sensorimotor regions in the PAE group showed less connectivity to certain hubs of the default mode network and more connectivity to areas of the salience network. Overall, our results show that despite similar patterns of organization in the sensorimotor network, subjects with PAE have increased FC between this network and other brain areas, perhaps suggesting overcompensation. These alterations in the sensorimotor network lay the foundation for future studies to evaluate interventions and treatments to improve motor function in children with PAE.

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Inter-subject Connectivity-Based Parcellation of a Patch of Cerebral Cortex

Cited by 21 publications

References 14 publications

Validation of consistent inter-subject connectivity-based parcellation

Validation of consistent inter-subject connectivity-based parcellation

A hierarchical method for whole‐brain connectivity‐based parcellation

Sensorimotor network alterations in children and youth with prenatal alcohol exposure

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