Top

International Journal of Computer Assisted Radiology and Surgery

Published in:

01-05-2014 | Original Article

Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis

Authors: Caspar J. Goch, Bram Stieltjes, Romy Henze, Jan Hering, Luise Poustka, Hans-Peter Meinzer, Klaus H. Maier-Hein

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 3/2014

Abstract

Purpose

Diagnosis of autism spectrum disorders (ASD) is difficult, as symptoms vary greatly and are difficult to quantify objectively. Recent work has focused on the assessment of non-invasive diffusion tensor imaging-based biomarkers that reflect the microstructural characteristics of neuronal pathways in the brain. While tractography-based approaches typically analyze specific structures of interest, a graph-based large-scale network analysis of the connectome can yield comprehensive measures of larger-scale architectural patterns in the brain. Commonly applied global network indices, however, do not provide any specificity with respect to functional areas or anatomical structures. Aim of this work was to assess the concept of network centrality as a tool to perform locally specific analysis without disregarding the global network architecture and compare it to other popular network indices.

Methods

We create connectome networks from fiber tractographies and parcellations of the human brain and compute global network indices as well as local indices for Wernicke’s Area, Broca’s Area and the Motor Cortex. Our approach was evaluated on 18 children suffering from ASD and 18 typically developed controls using magnetic resonance imaging-based cortical parcellations in combination with diffusion tensor imaging tractography.

Results

We show that the network centrality of Wernicke’s area is significantly (p \(<\) 0.001) reduced in ASD, while the motor cortex, which was used as a control region, did not show significant alterations. This could reflect the reduced capacity for comprehension of language in ASD.

Conclusions

The betweenness centrality could potentially be an important metric in the development of future diagnostic tools in the clinical context of ASD diagnosis. Our results further demonstrate the applicability of large-scale network analysis tools in the domain of region-specific analysis with a potential application in many different psychological disorders.

http://www.picsl.upenn.edu/ANTS/.

Aoki Y, Abe O, Nippashi Y, Yamasue H (2013) Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: a meta-analysis of diffusion tensor imaging tractography studies. Mol Autism 4(1):25PubMedCentralPubMedCrossRef

Baio J (2012) Prevalence of autism spectrum disorders autism and developmental disabilities monitoring network, 14 sites, united states, 2008. Department of Health and Human Services. Centers for Disease Control and Prevention, Morbidity and Mortality Weekly Report

Barttfeld P, Wicker B, Cukier S, Navarta S, Lew S, Leiguarda R, Sigman M (2012) State-dependent changes of connectivity patterns and functional brain network topology in autism spectrum disorder. Neuropsychologia 50(14):3653–3662PubMedCrossRef

Barttfeld P, Wicker B, Cukier S, Navarta S, Lew S, Sigman M (2011) A big-world network in asd: dynamical connectivity analysis reflects a deficit in long-range connections and an excess of short-range connections. Neuropsychologia 49(2):254–263PubMedCrossRef

Buckner RL, Sepulcre J, Talukdar T, Krienen FM, Liu H, Hedden T, Andrews-Hanna JR, Sperling RA, Johnson KA (2009) Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci 29(6):1860–1873PubMedCentralPubMedCrossRef

Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198PubMedCrossRef

Burns MS, Fahy J (2010) Brocas area: rethinking classical concepts from a neuroscience perspective. Top Stroke Rehabil 17:401–410PubMedCrossRef

Cauda F, Costa T, Palermo S, D’Agata F, Diano M, Bianco F, Duca S, Keller R (2013) Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study. Hum Brain Mapp. doi:10.1002/hbm.22313

Constantino JN, Davis SA, Todd RD, Schindler MK, Gross MM, Brophy SL, Metzger LM, Shoushtari CS, Splinter R, Reich W (2003) Validation of a brief quantitative measure of autistic traits: comparison of the social responsiveness scale with the autism diagnostic interview-revised. J Autism Dev Disord 33(4):427–433PubMedCrossRef

10.

Dehaene-Lambertz G, Hertz-Pannier L, Dubois J, Mériaux S, Roche A, Sigman M, Dehaene S (2006) Functional organization of perisylvian activation during presentation of sentences in preverbal infants. Proc Natl Acad Sci 103(38):14,240–14,245CrossRef

11.

Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Hyman BT, Albert MS, Killiany RJ (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31(3):968–980PubMedCrossRef

12.

DeWitt I, Rauschecker JP (2012) Phoneme and word recognition in the auditory ventral stream. Proc Natl Acad Sci USA 109(8):E505–E514

13.

Ecker C, Marquand A, Mouro-Miranda J, Johnston P, Daly EM, Brammer MJ, Maltezos S, Murphy CM, Robertson D, Williams SC, Murphy DGM (2010) Describing the brain in autism in five dimensions: magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J Neurosci 30(32):10,612–10,623CrossRef

14.

Fischl B, van der Kouwe A, Destrieux C, Halgren E, Ségonne F, Salat DH, Busa E, Seidman LJ, Goldstein J, Kennedy D, Caviness V, Makris N, Rosen B, Dale AM (2004) Automatically parcellating the human cerebral cortex. Cereb Cortex 14(1):11–22PubMedCrossRef

15.

Fletcher PT, Whitaker RT, Tao R, DuBray MB, Froehlich A, Ravichandran C, Alexander AL, Bigler ED, Lange N, Lainhart JE (2010) Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism. NeuroImage 51(3):1117–1125PubMedCentralPubMedCrossRef

16.

Ford A, Triplett W, Sudhyadhom A, Gullett JM, McGregor K, FitzGerald D, Mareci T, White K, Crosson B (2013) Brocas area and its striatal and thalamic connections: A diffusion-mri tractography study. Front Neuroanat 7:8. doi:10.3389/fnana.2013.00008

17.

Fornito A, Zalesky A, Breakspear M (2013) Graph analysis of the human connectome: promise, progress, and pitfalls. NeuroImage 80:426–444PubMedCrossRef

18.

Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry 40(1):35–41CrossRef

19.

Fritzsche KH, Neher PF, Reicht I, van Bruggen T, Goch C, Reisert M, Nolden M, Zelzer S, Meinzer HP, Stieltjes B (2012) Mitk diffusion imaging. Methods Inf Med 51(5):441–448

20.

Goch C, Stieltjes B, Henze R, Hering J, Meinzer HP, Fritzsche K (2013) Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis. In: Meinzer HP, Deserno TM, Handels H, Tolxdorff T (eds) Bildverarbeitung für die Medizin 2013, Informatik aktuell. Springer, Berlin, pp 51–56CrossRef

21.

Gotts SJ, Jo HJ, Wallace GL, Saad ZS, Cox RW, Martin A (2013) Two distinct forms of functional lateralization in the human brain. Proc Natl Acad Sci 110(36):E3435–E3444PubMedCentralPubMedCrossRef

22.

Greimel E, Nehrkorn B, Schulte-Rüther M, Fink G, Nickl-Jockschat T, Herpertz-Dahlmann B, Konrad K, Eickhoff S (2013) Changes in grey matter development in autism spectrum disorder. Brain Struct Funct 218(4):929–942PubMedCentralPubMedCrossRef

23.

Griffa A, Baumann PS, Thiran JP, Hagmann P (2013) Structural connectomics in brain diseases. NeuroImage 80:515–526PubMedCrossRef

24.

Groen W, Tesink C, Petersson K, van Berkum J, van der Gaag R, Hagoort P, Buitelaar J (2010) Semantic, factual, and social language comprehension in adolescents with autism: an FMRI study. Cereb Cortex 20(8):1937–1945PubMedCrossRef

25.

Howlin P (2003) Outcome in high-functioning adults with autism with and without early language delays: implications for the differentiation between autism and Asperger syndrome. J Autism Dev Disord 33(1):3–13PubMedCrossRef

26.

Howlin P, Goode S, Hutton J, Rutter M (2004) Adult outcome for children with autism. J Child Psychol Psychiatry 45(2):212–229PubMedCrossRef

27.

Ingalhalikar M, Parker D, Bloy L, Roberts TP, Verma R (2011) Diffusion based abnormality markers of pathology: toward learned diagnostic prediction of ASD. NeuroImage 57(3):918–927PubMedCentralPubMedCrossRef

28.

Jakab A, Emri M, Spisak T, Szeman-Nagy A, Beres M, Kis SA, Molnar P, Berenyi E (2013) Autistic traits in neurotypical adults: correlates of graph theoretical functional network topology and white matter anisotropy patterns. PLoS ONE 8(4):e60,982CrossRef

29.

Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM (2012) Fsl. NeuroImage 62(2):782–790PubMedCrossRef

30.

Johansen-Berg H (2013) Human connectomics what will the future demand? NeuroImage 80:541–544PubMedCrossRef

31.

Joseph RM, Fricker Z, Fenoglio A, Lindgren KA, Knaus TA, Tager-Flusberg H (2013) Structural asymmetries of language-related gray and white matter and their relationship to language function in young children with ASD. Brain Imaging Behav 1–13.

32.

Langen M, Schnack HG, Nederveen H, Bos D, Lahuis BE, de Jonge MV, van Engeland H, Durston S (2009) Changes in the developmental trajectories of striatum in autism. Biol Psychiatry 66(4):327–333PubMedCrossRef

33.

Lee JE, Bigler ED, Alexander AL, Lazar M, DuBray MB, Chung MK, Johnson M, Morgan J, Miller JN, McMahon WM, Lu J, Jeong EK, Lainhart JE (2007) Diffusion tensor imaging of white matter in the superior temporal gyrus and temporal stem in autism. Neurosci Lett 424(2):127–132PubMedCrossRef

34.

Lee JE, Chung MK, Lazar M, DuBray MB, Kim J, Bigler ED, Lainhart JE, Alexander AL (2009) A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis. NeuroImage 44(3):870–883PubMedCentralPubMedCrossRef

35.

Lewis WW, Sahin M, Scherrer B, Peters JM, Suarez RO, Vogel-Farley VK, Jeste SS, Gregas MC, Prabhu SP, Nelson CA, Warfield SK (2012) Impaired language pathways in tuberous sclerosis complex patients with autism spectrum disorders. Cereb Cortex 23(7):1526–1532

36.

Li H, Xue Z, Ellmore TM, Frye RE, Wong ST (2012) Network-based analysis reveals stronger local diffusion-based connectivity and different correlations with oral language skills in brains of children with high functioning autism spectrum disorders. Hum Brain Mapp 35(2):396–413

37.

Li Y, Liu Y, Li J, Qin W, Li K, Yu C, Jiang T (2009) Brain anatomical network and intelligence. PLoS Comput Biol 5(5): e1000395

38.

Lord C, Risi S, Lambrecht L, Leventhal B, DiLavore P, Pickles A, Rutter M (2000) The autism diagnostic observation schedulegeneric: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord 30(3):205–223PubMedCrossRef

39.

Lord C, Rutter M, Couteur A (1994) Autism diagnostic interview-revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord 24(5):659–685PubMedCrossRef

40.

McGrath J, Johnson K, O’Hanlon E, Garavan H, Gallagher L, Leemans A (2013) White matter and visuospatial processing in autism: a constrained spherical deconvolution tractography study. Autism Res 6(5):307–319PubMedCrossRef

41.

Mills BD, Lai J, Brown TT, Erhart M, Halgren E, Reilly J, Dale A, Appelbaum M, Moses P (2013) White matter microstructure correlates of narrative production in typically developing children and children with high functioning autism. Neuropsychologia 51(10):1933–1941

42.

Mueller S, Keeser D, Samson AC, Kirsch V, Blautzik J, Grothe M, Erat O, Hegenloh M, Coates U, Reiser MF, Hennig-Fast K, Meindl T (2013) Convergent findings of altered functional and structural brain connectivity in individuals with high functioning autism: a multimodal mri study. PLoS ONE 8(6):e67,329

43.

Nebel MB, Joel SE, Muschelli J, Barber AD, Caffo BS, Pekar JJ, Mostofsky SH (2012) Disruption of functional organization within the primary motor cortex in children with autism. Hum Brain Mapp 35(2):567–580

44.

Neher PF, Stieltjes B, Reisert M, Reicht I, Meinzer HP, Fritzsche KH (2012) MITK Global Tractography. In SPIE medical imaging 2012: image processing

45.

Nolden M, Zelzer S, Seitel A, Wald D, Müller M, Franz AM, Maleike D, Fangerau M, Baumhauer M, Maier-Hein L, Maier-Hein K, Meinzer HP, Wolf I (2013) The medical imaging interaction toolkit: challenges and advances. Int J Comput Assist Radiol Surg 8(4):607–620PubMedCrossRef

46.

Oldfield R (1971) The assessment and analysis of handedness: the edinburgh inventory. Neuropsychologia 9(1):97–113PubMedCrossRef

47.

Poustka L, Jennen-Steinmetz C, Henze R, Vomstein K, Haffner J, Stieltjes B (2012) Fronto-temporal disconnectivity and symptom severity in children with autism spectrum disorder. World J Biol Psychiatry 13(4):269–280PubMedCrossRef

48.

Raven JC, Court JH, Raven J (1995) Coloured progressive matrices. Psychologist Press, Oxford

49.

Rinehart NJ, Bradshaw JL, Brereton AV, Tonge BJ (2002) A clinical and neurobehavioural review of high-functioning autism and Asperger’s disorder. Aust N Z J Psychiatry 36(6):762–770PubMedCrossRef

50.

Roine U, Roine T, Salmi J, Nieminen-Von Wendt T, Leppämäki S, Rintahaka P, Tani P, Leemans A, Sams M (2013) Increased coherence of white matter fiber tract organization in adults with Asperger’s syndrome: a diffusion tensor imaging study. Autism Res 6(6):642–650

51.

Segonne F, Dale AM, Busa E, Glessner M, Salat D, Hahn HK, Fischl B (2004) A hybrid approach to the skull stripping problem in mri. NeuroImage 22(3):1060–1075PubMedCrossRef

52.

Seo EH, Lee DY, Lee JM, Park JS, Sohn BK, Lee DS, Choe YM, Woo JI (2013) Whole-brain functional networks in cognitively normal, mild cognitive impairment, and Alzheimers disease. PLoS ONE 8(1):e53,922CrossRef

53.

Sporns O (2013) The human connectome: origins and challenges. NeuroImage 80:53–61PubMedCrossRef

54.

Szaflarski JP, Rajagopal A, Altaye M, Byars AW, Jacola L, Schmithorst VJ, Schapiro MB, Plante E, Holland SK (2012) Left-handedness and language lateralization in children. Brain Res 1433:85–97PubMedCrossRef

55.

Travers BG, Adluru N, Ennis C, Tromp DPM, Destiche D, Doran S, Bigler ED, Lange N, Lainhart JE, Alexander AL (2012) Diffusion tensor imaging in autism spectrum disorder: a review. Autism Res 5(5):289–313

56.

Uddin LQ, Menon V, Young CB, Ryali S, Chen T, Khouzam A, Minshew NJ, Hardan AY (2011) Multivariate searchlight classification of structural magnetic resonance imaging in children and adolescents with autism. Biol Psychiatry 70(9):833–841PubMedCentralPubMedCrossRef

57.

Walker L, Gozzi M, Lenroot R, Thurm A, Behseta B, Swedo S, Pierpaoli C (2012) Diffusion tensor imaging in young children with autism: biological effects and potential confounds. Biol Psychiatry 72(12):1043–1051PubMedCentralPubMedCrossRef

Title: Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis
Authors: Caspar J. Goch
Bram Stieltjes
Romy Henze
Jan Hering
Luise Poustka
Hans-Peter Meinzer
Klaus H. Maier-Hein
Publication date: 01-05-2014
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 3/2014
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-014-0977-0

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis

Abstract

Purpose

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 3/2014

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model

Using the low-pass monogenic signal framework for cell/background classification on multiple cell lines in bright-field microscope images

Medical imaging informatics simulators: a tutorial

Surgical process modelling: a review

An automated insertion tool for cochlear implants with integrated force sensing capability

Co-registration of intra-operative brain surface photographs and pre-operative MR images