A wiring rule for the insula based on...
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A wiring rule for the insula based on DTI A.T. Baria, M.N. Baliki, E.L. Parks, A.V. Apkarian SFN 2009 Chicago 790.4/HH8 INTRODUCTION •Brain anatomy has been parcellated based on gross morphological features (Brodmann areas). Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL Connectivity-based clustering for single subjects 1 Sholl analysis implemented to extract geometric features of each tract 3 5 ANOVA reveals difference of tract shape between clusters One way analysis of variance (ANOVA) • Here we test the notion that brain parcellation exists based on local fiber tract branching patterns extending from small groups of neurons using diffusion tensor imaging (DTI) data of the human insula. • White matter connectivity-based parcellation (Johansen-Berg 2007) of the left insula was L ft l E l f b bili ti t t h d Sh ll l i One-way analysis of variance (ANOVA). One-way analysis of variance was performed for critical radius (top), exponential rise (middle), and exponential decay (bottom) of tract Sholl profiles across clusters. Significant differences between clusters were found for all 3 parameters: F-statistic p-value Critical Radius 12 24 <0 001 (Johansen-Berg, 2007) of the left insula was performed for 6 subjects. Common spatial clusters across subjects were further analyzed with Sholl analysis (Sholl, 1953) to assess branching patterns of the tracts within clusters. •We show that each cluster is associated with different tract shapes and that the insula can be organized based on geometric features of the Left panel: Example of probabilistic tractography and Sholl analysis performed for a single voxel of the left insula. The green shape represents the tract extracted for a single voxel. Sholl analysis consists of counting the number of intersections of the tract with concentric spheres centered around the seed voxel. Sphere radii (r) were incremented by 2mm. N denotes the number of intersections of the tract with the sphere radius. Right panel: Sholl profile of one tract. Sphere radial distance from the seed voxel is plotted along the x-axis and the number of tract voxels intersecting the sphere is plotted along the y-axis. Three parameters were extracted: exponential rise (blue line), critical radius (black ‘x’), and exponential decay (red line). Critical Radius 12.24 <0.001 Exponential Rise 9.22 <0.001 Exponential Decay 6.43 <0.001 tracts connecting it to the rest of the brain. METHODS • DTI images were acquired with a 3T scanner • White-matter tract insular clusters defined by whole- CONCLUSION Sholl profiles of conjunction clusters 4 Examples of connectivity-based parcellation from 6 subjects. Tractography was performed for each voxel within the left insula. Tracts associated with each voxel were clustered with g-means clustering, resulting in 7 – 11 clusters for each subject. Each colored shape group represents a line). (Siemens, Germany) using spin-echo echo-planar imaging on six healthy subjects. • Tracts at 316 voxels of the left insula for each subject were extracted with probabilistic tractography (FSL software; fmrib, Smith et al. 2001). Voxels were clustered based on tractograms using g-means clustering (Hamerly, 2003) and an across-subject cluster conjunction brain connectivity show distinct branching pattern characteristics. • Critical radius, exponential rise, and exponential decay of white-matter tracts extending from the insula were significantly different across clusters and were common across subjects. • These results indicate that the insula is composed of diff t i b d hit tt t 7 11 clusters for each subject. Each colored shape group represents a different cluster. Axes are scaled in millimeters. The x-axis is lateral-medial, the y-axis is posterior-anterior, and the z-axis is inferior-superior along the neurological axis. 2 DTI-connectivity conjunction map results in 5 clusters map was formed (panel 1 and panel 2). • Sholl analysis (Sholl, 1953) was performed on each tract within each cluster using an in-house Matlab algorithm (panel 3). •Exponential rise, decay, and critical radius were extracted from each tract’s Sholl profile (panel 3). different regions based on white-matter geometry which parallels the well-established idea that neural structures can be segregated based on physical features at different scales. •We suggest that the brain can be organized based on connectivity-independent measures of white matter tracts, offering a new dimension along which to classify brain structures. Sholl profiles of clusters shared across all subjects. The cluster number corresponds to that shown in panel 2. Each thin line represents the Sholl profile of a single tract from one subject. The thick blue line is the Funded by NIH NINDS NS35115 • One-way analysis of variance was performed for exponential rise, decay, and critical radius of each cluster to assess the statistical differences in tract branching patterns across clusters (panel 5). average Sholl profile across all subjects for that cluster. The sphere radial distance from the seed voxel is shown on the x-axis and is marked in millimeters. The y-axis is the standardized number of tract voxels intersecting the sphere (see panel 3). Cluster conjunction map of 6 subjects resulting in 5 common clusters across subjects. Single subject cluster maps were overlain and thresholded for spatial overlap across all subjects. Each shape group represents a different cluster. Numbers denote cluster identification. Axes are scaled in millimeters.
Transcript of A wiring rule for the insula based on...
A wiring rule for the insula based on DTIA.T. Baria, M.N. Baliki, E.L. Parks, A.V. Apkarian
SFN 2009Chicago
790.4/HH8
INTRODUCTION
•Brain anatomy has been parcellated based on gross morphological features (Brodmann areas).
Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL
Connectivity-based clustering for single subjects
1 Sholl analysis implemented to extract geometric features of each tract
3 5 ANOVA reveals difference of tract shape between clusters
One way analysis of variance (ANOVA)
• Here we test the notion that brain parcellation exists based on local fiber tract branching patterns extending from small groups of neurons using diffusion tensor imaging (DTI) data of the human insula.
• White matter connectivity-based parcellation (Johansen-Berg 2007) of the left insula was L ft l E l f b bili ti t t h d Sh ll l i
One-way analysis of variance (ANOVA). One-way analysis of variance was performed for critical radius (top), exponential rise (middle), and exponential decay (bottom) of tract Sholl profiles across clusters.
Significant differences between clusters were found for all 3 parameters:
F-statistic p-valueCritical Radius 12 24 <0 001(Johansen-Berg, 2007) of the left insula was
performed for 6 subjects. Common spatial clusters across subjects were further analyzed with Sholl analysis (Sholl, 1953) to assess branching patterns of the tracts within clusters.
•We show that each cluster is associated with different tract shapes and that the insula can be organized based on geometric features of the
Left panel: Example of probabilistic tractography and Sholl analysis performed for a single voxel of the left insula. The green shape represents the tract extracted for a single voxel. Sholl analysis consists of counting the number of intersections of the tract with concentric spheres centered around the seed voxel. Sphere radii (r) were incremented by 2mm. N denotes the number of intersections of the tract with the sphere radius.
Right panel: Sholl profile of one tract. Sphere radial distance from the seed voxel is plotted along the x-axis and the number of tract voxels intersecting the sphere is plotted along the y-axis. Three parameters were extracted: exponential rise (blue line), critical radius (black ‘x’), and exponential decay (red line).
Critical Radius 12.24 <0.001
Exponential Rise 9.22 <0.001
Exponential Decay 6.43 <0.001
g gtracts connecting it to the rest of the brain.
METHODS• DTI images were acquired with a 3T scanner • White-matter tract insular clusters defined by whole-
CONCLUSION
Sholl profiles of conjunction clusters4
Examples of connectivity-based parcellation from 6 subjects. Tractography was performed for each voxel within the left insula. Tracts associated with each voxel were clustered with g-means clustering, resulting in 7 – 11 clusters for each subject. Each colored shape group represents a
line).
(Siemens, Germany) using spin-echo echo-planarimaging on six healthy subjects.
• Tracts at 316 voxels of the left insula for eachsubject were extracted with probabilistictractography (FSL software; fmrib, Smith et al.2001). Voxels were clustered based ontractograms using g-means clustering (Hamerly,2003) and an across-subject cluster conjunction
ybrain connectivity show distinct branching patterncharacteristics.
• Critical radius, exponential rise, and exponentialdecay of white-matter tracts extending from the insulawere significantly different across clusters and werecommon across subjects.
• These results indicate that the insula is composed ofdiff t i b d hit tt t
7 11 clusters for each subject. Each colored shape group represents a different cluster. Axes are scaled in millimeters. The x-axis is lateral-medial, the y-axis is posterior-anterior, and the z-axis is inferior-superior along the neurological axis.
2 DTI-connectivity conjunction map results in 5 clusters
map was formed (panel 1 and panel 2).
• Sholl analysis (Sholl, 1953) was performed oneach tract within each cluster using an in-houseMatlab algorithm (panel 3).
•Exponential rise, decay, and critical radius wereextracted from each tract’s Sholl profile (panel3).
different regions based on white-matter geometrywhich parallels the well-established idea that neuralstructures can be segregated based on physicalfeatures at different scales.
•We suggest that the brain can be organized based onconnectivity-independent measures of white mattertracts, offering a new dimension along which to classifybrain structures.
Sholl profiles of clusters shared across all subjects. The cluster number corresponds to that shown in panel 2. Each thin line represents the Sholl profile of a single tract from one subject. The thick blue line is the
Funded by NIH NINDS NS35115
• One-way analysis of variance was performedfor exponential rise, decay, and critical radius ofeach cluster to assess the statistical differencesin tract branching patterns across clusters (panel5).
javerage Sholl profile across all subjects for that cluster. The sphere radial distance from the seed voxel is shown on the x-axis and is marked in millimeters. The y-axis is the standardized number of tract voxels intersecting the sphere (see panel 3).
Cluster conjunction map of 6 subjects resulting in 5 common clusters across subjects. Single subject cluster maps were overlain and thresholded for spatial overlap across all subjects. Each shape group represents a different cluster. Numbers denote cluster identification. Axes are scaled in millimeters.
