Connectogram

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Connectograms are graphical representations of connectomics, the field of study dedicated to mapping and interpreting all of the white matter fiber connections in the human brain. These circular graphs based on Diffusion MRI data utilize graph theory to demonstrate the white matter connections and cortical characteristics for single structures, single subjects, or populations.

Structure[edit]

Connectogram showing average connections and cortical measures of 110 normal, right-handed males, aged 25-36.
Legend for metadata presented in the various rings of the connectogram.

Background and description[edit]

Circular representations of connections have been used in a number of disciplines; examples include representation of aspects of epidemics,[1] geographical networks,[2] musical beats,[3] diversity in bird populations,[4] and genomic data.[5] The connectogram, as a graphical representation of brain connectomics, was proposed in 2012.[6]

Brains colored according to the outer ring of the connectogram.

Connectograms are circular, with the left half depicting the left hemisphere and the right half depicting the right hemisphere. The hemispheres are further broken down into frontal lobe, insular cortex, limbic lobe, temporal lobe, parietal lobe, occipital lobe, subcortical structures, and cerebellum. At the bottom the brain stem is also represented between the two hemispheres. Within these lobes, each cortical area is labeled with an abbreviation and assigned its own color, which can be used to designate these same cortical regions in other figures, such as the parcellated brain surfaces in the image to the right, so that the reader can find the corresponding cortical areas on a geometrically accurate surface and see exactly how disparate the connected regions may be. Inside the cortical surface ring, the concentric circles each represent different attributes of the corresponding cortical regions. In order from outermost to innermost, these metric rings represent the grey matter volume, surface area, cortical thickness, curvature, and degree of connectivity (the relative proportion of fibers initiating or terminating in the region compared to the whole brain). Inside these circles, lines connect regions that are found to be structurally connected. The relative density (number of fibers) of these connections is reflected in the opacity of the lines, so that one can easily compare various connections and their structural importance. The fractional anisotropy of each connection is reflected in its color.[6]

Uses[edit]

Brain mapping[edit]

With the recent concerted push to map all of the human brain and its connections,[7][8] it has become increasingly important to find ways to graphically represent the large amounts of data involved in connectomics. Most other representations of the connectome use 3 dimensions, and therefore require an interactive graphical user interface.[6] The connectogram can display 83 cortical regions within each hemisphere, and visually display which areas are structurally connected, all on a flat surface. It is therefore conveniently filed in patient records, or to display in print.

Clinical use[edit]

Connectogram, typical of those in clinical use, depicting estimated connection damage in Phineas Gage, who in 1848 survived a large iron bar being propelled through his skull and brain. The connectogram shows only the connections that were estimated to be damaged.

On an individual level, connectograms can be used to inform the treatment of patients with neuroanatomical abnormalities. Connectograms have been used to monitor the progression of neurological recovery of patients who suffered a traumatic brain injury (TBI).[9] They have also been applied to famous patient Phineas Gage, to estimate damage to his neural network (as well as the damage at the cortical level—the primary focus of earlier studies on Gage).[10]

Empirical study[edit]

Connectograms can represent the averages of cortical metrics (grey matter volume, surface area, cortical thickness, curvature, and degree of connectivity), as well as tractography data, such as the average densities and fractional anisotropy of the connections, across populations of any size. This allows for visual and statistical comparison between groups such as males and females,[11] differing age cohorts, or healthy controls and patients. Some versions have been used to analyze how partitioned networks are in patient populations[12] or the relative balance between inter- and intra-hemispheric connections.[13]

Modified versions[edit]

There are many possibilities for which measures are included in the rings of a connectogram. Irimia and Van Horn (2012) have published connectograms which examine the correlative relationships between regions and uses the figures to compare the approaches of graph theory and connectomics.[14] Some have been published without the inner circles of cortical metrics.[15] Others include additional measures relating to neural networks,[16] which can be added as additional rings to the inside to show metrics of graph theory, as in the extended connectogram here:

A connectogram of a healthy control subject, and includes 5 additional nodal measures not included in the standard connectogram. From outside to inside, the rings represent the cortical region, grey matter volume, surface area, cortical thickness, curvature, degree of connectivity, node strength, betweenness centrality, eccentricity, nodal efficiency, and eigenvector centrality. Between degree of connectivity and node strength, a blank ring has been added as a placeholder.

Regions and their abbreviations[edit]

Acronym Region in connectogram
ACgG/S Anterior part of the cingulate gyrus and sulcus
ACirInS Anterior segment of the circular sulcus of the insula
ALSHorp Horizontal ramus of the anterior segment of the lateral sulcus (or fissure)
ALSVerp Vertical ramus of the anterior segment of the lateral sulcus (or fissure)
AngG Angular gyrus
AOcS Anterior occipital sulcus and preoccipital notch (temporo-occipital incisure)
ATrCoS Anterior transverse collateral sulcus
CcS Calcarine sulcus
CgSMarp Marginal branch (or part) of the cingulate sulcus
CoS/LinS Medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus
CS Central sulcus (Rolando’s fissure)
Cun Cuneus
FMarG/S Fronto-marginal gyrus (of Wernicke) and sulcus
FuG Lateral occipito-temporal gyrus (fusiform gyrus)
HG Heschl’s gyrus (anterior transverse temporal gyrus)
InfCirInS Inferior segment of the circular sulcus of the insula
InfFGOpp Opercular part of the inferior frontal gyrus
InfFGOrp Orbital part of the inferior frontal gyrus
InfFGTrip Triangular part of the inferior frontal gyrus
InfFS Inferior frontal sulcus
InfOcG/S Inferior occipital gyrus and sulcus
InfPrCS Inferior part of the precentral sulcus
IntPS/TrPS Intraparietal sulcus (interparietal sulcus) and transverse parietal sulci
InfTG Inferior temporal gyrus
InfTS Inferior temporal sulcus
JS Sulcus intermedius primus (of Jensen)
LinG Lingual gyrus, lingual part of the medial occipito-temporal gyrus
LOcTS Lateral occipito-temporal sulcus
LoInG/CInS Long insular gyrus and central insular sulcus
LOrS Lateral orbital sulcus
MACgG/S Middle-anterior part of the cingulate gyrus and sulcus
MedOrS Medial orbital sulcus (olfactory sulcus)
MFG Middle frontal gyrus
MFS Middle frontal sulcus
MOcG Middle occipital gyrus, lateral occipital gyrus
MOcS/LuS Middle occipital sulcus and lunatus sulcus
MPosCgG/S Middle-posterior part of the cingulate gyrus and sulcus
MTG Middle temporal gyrus
OcPo Occipital pole
OrG Orbital gyri
OrS Orbital sulci (H-shaped sulci)
PaCL/S Paracentral lobule and sulcus
PaHipG Parahippocampal gyrus, parahippocampal part of the medial occipito-temporal gyrus
PerCaS Pericallosal sulcus (S of corpus callosum)
POcS Parieto-occipital sulcus (or fissure)
PoPl Polar plane of the superior temporal gyrus
PosCG Postcentral gyrus
PosCS Postcentral sulcus
PosDCgG Posterior-dorsal part of the cingulate gyrus
PosLS Posterior ramus (or segment) of the lateral sulcus (or fissure)
PosTrCoS Posterior transverse collateral sulcus
PosVCgG Posterior-ventral part of the cingulate gyrus (isthmus of the cingulate gyrus)
PrCG Precentral gyrus
PrCun Precuneus
RG Straight gyrus (gyrus rectus)
SbCaG Subcallosal area, subcallosal gyrus
SbCG/S Subcentral gyrus (central operculum) and sulci
SbOrS Suborbital sulcus (sulcus rostrales, supraorbital sulcus)
SbPS Subparietal sulcus
ShoInG Short insular gyri
SuMarG Supramarginal gyrus
SupCirInS Superior segment of the circular sulcus of the insula
SupFG Superior frontal gyrus
SupFS Superior frontal sulcus
SupOcG Superior occipital gyrus
SupPrCS Superior part of the precentral sulcus
SupOcS/TrOcS Superior occipital sulcus and transverse occipital sulcus
SupPL Superior parietal lobule
SupTGLp Lateral aspect of the superior temporal gyrus
SupTS Superior temporal sulcus
TPl Temporal plane of the superior temporal gyrus
TPo Temporal pole
TrFPoG/S Transverse frontopolar gyri and sulci
TrTS Transverse temporal sulcus
Amg Amygdala
CaN Caudate nucleus
Hip Hippocampus
NAcc Nucleus accumbens
Pal Pallidum
Pu Putamen
Tha Thalamus
CeB Cerebellum
BStem Brain stem

See also[edit]

References[edit]

  1. ^ Guo, Zhenyang et al. (January 2013). "National Borders Effectively Halt the Spread of Rabies: The Current Rabies Epidemic in China Is Dislocated from Cases in Neighboring Countries". PLoS Neglected Tropical Diseases 7 (1): e2039. doi:10.1371/journal.pntd.0002039. PMID 23383359. 
  2. ^ Hennemann, Stefan (2013). "Information-rich visualisation of dense geographical networks". Journal of Maps 9 (1): 1–8. doi:10.1080/17445647.2012.753850. 
  3. ^ Lamere, Paul. "The Infinite Jukebox". Music Machinery. 
  4. ^ Jetz, W.; G. H. Thomas; J. B. Joy; K. Hartmann; A. O. Mooers (15 November 2012). "The global diversity of birds in space and time.". Nature 491 (7424): 444–448. doi:10.1038/nature11631. PMID 23123857. 
  5. ^ Yip, Kevin et al. (26 September 2012). "Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors". Genome Biology 13 (9): R48. doi:10.1186/gb-2012-13-9-r48. PMID 22950945. 
  6. ^ a b c Irimia, Andrei; Chambers, M.C.; Torgerson, C.M.; Van Horn, J.D. (2 April 2012). "Circular representation of human cortical networks for subject and population-level connectomic visualization". Neuroimage 60 (2): 1340–51. doi:10.1016/j.neuroimage.2012.01.107. PMC 3594415. PMID 22305988. 
  7. ^ "Human Connectome Project". NIH. 
  8. ^ "Hard Cell". The Economist. 9 March 2013. Retrieved 11 March 2013. 
  9. ^ Irimia, Andrei; Chambers, M.C.; Torgerson, C.M.; Filippou, M.; Hovda, D.A.; Alger, J.R.; Gerig, G.; Toga, A.W.; Vespa, P.M.; Kikinis, R.; Van Horn, J.D. (6 February 2012). "Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury". Frontiers in Neurology 3: 10. doi:10.3389/fneur.2012.00010. PMC 3275792. PMID 22363313. 
  10. ^ Van Horn, John D.; Irimia, A.; Torgerson, C.M.; Chambers, M.C.; Kikinis, R.; Toga, A.W. (16 May 1012). Sporns, Olaf, ed. "Mapping connectivity damage in the case of Phineas Gage". PLoS ONE 7 (5): e37454. doi:10.1371/journal.pone.0037454. PMC 3353935. PMID 22616011. 
  11. ^ Ingalhalikar, Madhura; Alex Smith; Drew Parker; Theodore Satterthwaite; Mark Elliott; Kosha Ruparel; Hakon Hakonarson; Raquel Gur; Ragini Verma (December 2013). "Sex differences in the structural connectome of the human brain". Proceedings of the National Academy of Sciences (PNAS) 111 (2): 823–8. doi:10.1073/pnas.1316909110. PMID 24297904. 
  12. ^ Messé, Arnaud; Sophie Caplain; Mélanie Pélégrini-Issac; Sophie Blancho; Richard Lévy; Nozar Aghakhani; Michèle Montreuil; Habib Benali; Stéphane Lehéricy (6 June 2013). "Specific and Evolving Resting-State Network Alterations in Post-Concussion Syndrome Following Mild Traumatic Brain Injury". PLoS ONE 8 (6): e65470. doi:10.1371/journal.pone.0065470. PMID 23755237. 
  13. ^ Wee, Chong-Yaw; Pew-Thian Yap; Daoqiang Zhang; Lihong Wang; Dinggang Shen (7 March 2013). "Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification". Brain Structure & Function 219: 641–656. doi:10.1007/s00429-013-0524-8. PMID 23468090. 
  14. ^ Irimia, Andrei; Jack Van Horn (29 October 2012). "The structural, connectomic, and network covariance of the human brain". Neuroimage 66: 489–499. doi:10.1016/j.neuroimage.2012.10.066. PMC 3586751. PMID 23116816. 
  15. ^ Pandit, A.S.; Robinson E; Aljabar P; Ball G; Gousias IS; Wang Z; Hajnal JV; Rueckert D; Counsell SJ; Montana G; Edwards AD (31 March 2013). "Whole-Brain Mapping of Structural Connectivity in Infants Reveals Altered Connection Strength Associated with Growth and Preterm Birth". Cerebral Cortex 24: 2324–2333. doi:10.1093/cercor/bht086. PMID 23547135. 
  16. ^ Sporns, Olaf (2011). Networks of the Brain. MIT Press. ISBN 978-0-262-01469-4. 

Further reading[edit]

[further 1][further 2][further 3]

  1. ^ Petrella, Jeffrey; P. Murali Doraiswamy (9 April 2013). "From the bridges of Königsberg to the fields of Alzheimer". Neurology 80 (15): 1360–2. doi:10.1212/WNL.0b013e31828c3062. PMID 23486887. 
  2. ^ Craddock, R Cameron; Saad Jbabdi; Chao-Gan Yan; Joshua T Vogelstein; F Xavier Castellanos; Adriana Di Martino; Clare Kelly; Keith Heberlein; Stan Colcombe; Michael P Milham (June 2013). "Imaging human connectomes at the macroscale". Nature Methods 10 (6): 524–39. doi:10.1038/nmeth.2482. PMID 23722212. 
  3. ^ Margulies, Daniel; Joachim Böttger; Aimi Watanabe; Krzysztof J. Gorgolewski (15 October 2013). "Visualizing the human connectome". Neuroimage 80: 445–61. doi:10.1016/j.neuroimage.2013.04.111. PMID 23660027.