Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects

Schiffler, Patrick; Tenberge, Jan-Gerd; Wiendl, Heinz; Meuth, Sven G.

doi:10.3389/fnhum.2017.00352

Cited by 9 publications

(5 citation statements)

References 49 publications

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“…In order to assess the existence of regional WM atrophy in the hemisphere with the thalamic lesion, the Freesurfer 6.0 software (Schiffler et al 2017) was used to automatically segment the WM into 34 areas per hemisphere of the Desikan-Killiany atlas (Desikan et al 2006). Special care was taken to deal with the enlarged ventricles of the patients to ensure an accurate segmentation, by manually adjusting the parameters of the semi-automatic procedure.…”

Section: Structural Volumetrymentioning

confidence: 99%

Regional White Matter Atrophy Correlates with Spike Activity in Encephalopathy Related to Status Epilepticus During Slow Sleep (ESES) After Early Thalamic Lesions

et al. 2020

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Encephalopathy related to Status Epilepticus during slow Sleep (ESES) is an age-related, epileptic syndrome, which associates cognitive/behavioral disturbances with a peculiar pattern of spike activity. One promising line of research is the study of ESES in cases of early thalamic lesions. We studied 7 ESES patients with unilateral thalamic lesions using magnetic resonance imaging to assess regional white matter (WM) and thalamic nuclei volume differences, and long-term electroencephalogram recordings to localize the epileptogenic cortex. N170 event-related potentials were used to demonstrate the dysfunctional character of the WM abnormalities. Diffusion-weighted images in a subset of 4 patients were used to parcellate the thalamus and evaluate volume asymmetries, based on cortical connectivity. Large WM regional atrophy in the hemisphere with the thalamic lesion was associated with both cortical dysfunction and epileptic activity. A correlation was demonstrated between lesions in the pulvinar and the mediodorsal thalamic nuclei and WM atrophy of the corresponding cortical projection areas. We propose that these abnormalities are due to the widespread structural disconnection produced by the thalamic lesions associated to a yet unknown age-dependent factor. Further exploration of WM regional atrophy association with the spike activity in other etiologies could lend support to the cortical disconnection role in ESES genesis.

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Section: Structural Volumetrymentioning

confidence: 99%

Regional White Matter Atrophy Correlates with Spike Activity in Encephalopathy Related to Status Epilepticus During Slow Sleep (ESES) After Early Thalamic Lesions

et al. 2020

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“…For an inter-subject analysis, it is also necessary to find the correspondence between subjects. One strategy is to create the parcellation taking into account the main connections present in the population of subjects (Schiffler et al, 2017 ). Another approach is to detect individual connectivity patterns, or even parcels, from the tractography of each subject and to then find consistent parcels among the population of subjects (Moreno-Dominguez et al, 2014 ; Lefranc et al, 2016 ; Li et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

From Coarse to Fine-Grained Parcellation of the Cortical Surface Using a Fiber-Bundle Atlas

López-López

Vázquez

Houenou

et al. 2020

Front. Neuroinform.

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In this article, we present a hybrid method to create fine-grained parcellations of the cortical surface, from a coarse-grained parcellation according to an anatomical atlas, based on cortico-cortical connectivity. The connectivity information is obtained from segmented superficial and deep white matter bundles, according to bundle atlases, instead of the whole tractography. Thus, a direct matching between the fiber bundles and the cortical regions is obtained, avoiding the problem of finding the correspondence of the cortical parcels among subjects. Generating parcels from segmented fiber bundles can provide a good representation of the human brain connectome since they are based on bundle atlases that contain the most reproducible short and long connections found on a population of subjects. The method first processes the tractography of each subject and extracts the bundles of the atlas, based on a segmentation algorithm. Next, the intersection between the fiber bundles and the cortical mesh is calculated, to define the initial and final intersection points of each fiber. A fiber filtering is then applied to eliminate misclassified fibers, based on the anatomical definition of each bundle and the labels of Desikan-Killiany anatomical parcellation. A parcellation algorithm is then performed to create a subdivision of the anatomical regions of the cortex, which is reproducible across subjects. This step resolves the overlapping of the fiber bundle extremities over the cortical mesh within each anatomical region. For the analysis, the density of the connections and the degree of overlapping, is considered and represented with a graph. One of our parcellations, an atlas composed of 160 parcels, achieves a reproducibility across subjects of ≈0.74, based on the average Dice's coefficient between subject's connectivity matrices, rather than ≈0.73 obtained for a macro anatomical parcellation of 150 parcels. Moreover, we compared two of our parcellations with state-of-the-art atlases, finding a degree of similarity with dMRI, functional, anatomical, and multi-modal atlases. The higher similarity was found for our parcellation composed of 185 sub-parcels with another parcellation based on dMRI data from the same database, but created with a different approach, leading to 130 parcels in common based on a Dice's coefficient ≥0.5.

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“…The Freesurfer 6.0 software ( Schiffler et al, 2017 ) was used to delineate each subject’s Brodmann areas 17 and 18 ( Fischl et al, 2008 ) from their MPRAGE image, corresponding to the primary (V1) and secondary (V2) visual cortical areas, respectively. These regions of interest (ROIs), henceforth called “V1V2”, were grouped and registered to the diffusion data using FMRIB’s Linear Image Registration Tool ( Jenkinson and Smith, 2001 ).…”

Section: Methodsmentioning

confidence: 99%

In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data

et al. 2022

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PurposeWe present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.TheoryThe proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β.MethodsMRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract.ResultsThe estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm−α.ConclusionThe estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.

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Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects

Cited by 9 publications

References 49 publications

Regional White Matter Atrophy Correlates with Spike Activity in Encephalopathy Related to Status Epilepticus During Slow Sleep (ESES) After Early Thalamic Lesions

Regional White Matter Atrophy Correlates with Spike Activity in Encephalopathy Related to Status Epilepticus During Slow Sleep (ESES) After Early Thalamic Lesions

From Coarse to Fine-Grained Parcellation of the Cortical Surface Using a Fiber-Bundle Atlas

In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data

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