Abstract
Autism spectrum disorder (ASD) is characterized by abnormal functional organization of brain networks, which may underlie the cognitive and social impairments observed in affected individuals. The present study characterizes unique intrinsic connectivity within- and between- neural networks in children through to adults with ASD, relative to controls. Resting state fMRI data were analyzed in 204 subjects, 102 with ASD and 102 age- and sex-matched controls (ages 7–40 years), acquired on a single scanner. ASD was assessed using the autism diagnostic observation schedule (ADOS). BOLD correlations were calculated between 47 regions of interest, spanning seven resting state brain networks. Partial least squares (PLS) analyses evaluated the association between connectivity patterns and ASD diagnosis as well as ASD severity scores. PLS demonstrated dissociable connectivity patterns in those with ASD, relative to controls. Similar patterns were observed in the whole cohort and in a subgroup analysis of subjects under 18 years of age. Greater inter-network connectivity was seen in ASD with greater intra-network connectivity in controls. In conclusion, stronger inter-network and weaker intra-network resting state-fMRI BOLD correlations characterize ASD and may differentiate control and ASD cohorts. These findings are relevant to understanding ASD as a disruption of network topology.
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References
Assaf M, Jagannathan K, Calhoun VD, Miller L, Stevens MC, Sahl R, O’boyle JG, Schultz RT, Pearlson GD (2010) Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients. NeuroImage 53(1):247–256. https://doi.org/10.1016/j.neuroimage.2010.05.067
Beckmann CF, Beckmann CF, Smith SM, Smith SM (2004) Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans Med Imaging 23(2):137–152. https://doi.org/10.1109/TMI.2003.822821
Bernas A, Barendse EM, Aldenkamp AP, Backes WH, Hofman PAM, Hendriks MPH, Kessels RP, Willems FM, de With PH, Zinger S, Jansen JFA (2018) Brain resting-state networks in adolescents with high-functioning autism: analysis of spatial connectivity and temporal neurodynamics. Brain Behav 8(2):1–10. https://doi.org/10.1002/brb3.878
Birn RM, Molloy EK, Patriat R, Parker T, Meier TB, Kirk GR, Nair VA, Meyerand ME, Prabhakaran V (2013) The effect of scan length on the reliability of resting-state fMRI connectivity estimates. NeuroImage 83:550–558. https://doi.org/10.1016/j.neuroimage.2013.05.099
Brier MR, Thomas JB, Snyder AZ, Benzinger TL, Zhang D, Raichle ME, Holtzman DM, Morris JC, Ances BM (2012) Loss of intra- and inter-network resting state functional connections with alzheimer’s disease progression. J Neurosci 32(26):8890–8899. https://doi.org/10.1523/JNEUROSCI.5698-11.2012.Loss
Carper RA, Solders S, Treiber JM, Fishman I, Müller RA (2015) Corticospinal tract anatomy and functional connectivity of primary motor cortex in autism. J Am Acad Child Adolesc Psychiatry 54(10):859–867. https://doi.org/10.1016/j.jaac.2015.07.007
Chen CP, Keown CL, Jahedi A, Nair A, Pflieger ME, Bailey BA, Müller R-A (2015) Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism. NeuroImage Clin 8:238–245. https://doi.org/10.1016/j.nicl.2015.04.002
Chien Y-L, Gau SS-F, Shang C-Y, Chiu Y-N, Tsai W-C, Wu Y-Y (2015) Visual memory and sustained attention impairment in youths with autism spectrum disorders. Psychol Med 45(11):2263–2273. https://doi.org/10.1017/S0033291714003201
Cox RW (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res Int J, 29(3), 162–173. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/8812068
De Pasquale F, Della Penna S, Snyder AZ, Marzetti L, Pizzella V, Luca G (2000) Supplemental information a cortical core for dynamic integration of functional networks in the resting human brain. Neuron 74, 1–21
de Pasquale F, Della Penna S, Snyder AZ, Marzetti L, Pizzella V, Romani GL, Corbetta M (2012) A cortical core for dynamic integration of functional networks in the resting human brain. Neuron 74(4):753–764. https://doi.org/10.1016/j.neuron.2012.03.031
Dosenbach NUF, Nardos B, Cohen AL, Fair DA, Power D, Church JA, Nelson SM, Wig GS, Vogel AC, Lessov-Schlaggar CN, Barnes KA, Dubis JW, Feczko E, Coalson RS, Pruett JR Jr, Barch DM, Petersen SE, Schlaggar BL (2011) Prediction of individual brain maturity using fMRI. Science 329(5997):1358–1361. https://doi.org/10.1126/science.1194144.Prediction
Doyle-Thomas KaR, Lee W, Foster NEV, Tryfon A, Ouimet T, Hyde KL, Evans AC, Lewis J, Zwaigenbaum L, Anagnostou E (2015) Atypical functional brain connectivity during rest in autism spectrum disorders. Ann Neurol, 866–876. https://doi.org/10.1002/ana.24391
Fair DA, Cohen AL, Power JD, Dosenbach NUF, Church J, Miezin FM, Schlaggar BL, Petersen SE (2009) Functional brain networks develop from a “local to distributed” organization. PLoS Comput Biol 5(5):e1000381. https://doi.org/10.1371/journal.pcbi.1000381
Fishman I, Keown CL, Lincoln AJ, Pineda J, Müller R-A (2014) Atypical cross talk between mentalizing and mirror neuron networks in autism spectrum disorder. JAMA Psychiatr 71(7):751–760. https://doi.org/10.1001/jamapsychiatry.2014.83
Floris DL, Barber AD, Nebel MB, Martinelli M, Lai M-C, Crocetti D, Baron-Cohen S, Suckling J, Pekar JJ, Mostofsky SH (2016) Atypical lateralization of motor circuit functional connectivity in children with autism is associated with motor deficits. Mol Autism 7(1):35. https://doi.org/10.1186/s13229-016-0096-6
Gotham K, Pickles A, Lord C (2009) Standardizing ADOS scores for a measure of severity in autism spectrum disorders. J Autism Dev Disord 39(5):693–705. https://doi.org/10.1007/s10803-008-0674-3
Hahamy A, Behrmann M, Malach R (2015) The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder. Nat Neurosci, 18(2). https://doi.org/10.1038/nn.3919
Ho DE, Imai K, King G, Stuart EA (2011) MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Softw 42(8):1–28. https://doi.org/10.18637/jss.v042.i08
Hus V, Lord C (2014) Effects of child characteristics on the Autism diagnostic interview-revised: implications for use of scores as a measure of ASD severity. J Autism Dev Disord 43(2):371–381. https://doi.org/10.1007/s10803-012-1576-y
Ibrahim GM, Morgan BR, Lee W, Smith ML, Donner EJ, Wang F, Beers CA, Federico P, Taylor MJ, Doesburg SM, Rutka JT, Carter Snead O (2014) Impaired development of intrinsic connectivity networks in children with medically intractable localization-related epilepsy. Hum Brain Mapp 35(11):5686–5700. https://doi.org/10.1002/hbm.22580
Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM (2012) FSL NeuroImage 62(2):782–790. https://doi.org/10.1016/j.neuroimage.2011.09.015
Kana RK, Libero LE, Moore MS (2011) Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders. Phys Life Rev 8(4):410–437. https://doi.org/10.1016/j.plrev.2011.10.001
Kennedy DP, Redcay E, Courchesne E (2006) Failing to deactivate: resting functional abnormalities in autism. Proc Natl Acad Sci USA 103(21):8275–8280. https://doi.org/10.1073/pnas.0600674103
Keown C, Shih P, Nair A, Peterson N, Mulvey M, Müller RA (2013) Local functional overconnectivity in posterior brain regions is associated with symptom severity in autism spectrum disorders. Cell Rep 5(3):567–572. https://doi.org/10.1016/j.celrep.2013.10.003
Loomes R, Hull L, Mandy WPL (2017) What is the male-to-female ratio in autism spectrum disorder? a systematic review and meta-analysis. J Am Acad Child Psy 56(6):466–474. https://doi.org/10.1016/j.jaac.2017.03.013
Lord C, Risi S, Lambrecht L, Cook EH, Leventhal BL, Dilavore PC, Pickles A, Rutter M (2000) The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord 30(3):205–23
McIntosh AR, Lobaugh NJ (2004) Partial least squares analysis of neuroimaging data: applications and advances. NeuroImage, 23(Suppl 1):S250–63. https://doi.org/10.1016/j.neuroimage.2004.07.020
McIntosh AR, Mišić B (2013) Multivariate statistical analyses for neuroimaging data. Annu Rev Psychol 64:499–525. https://doi.org/10.1146/annurev-psych-113011-143804
McKinnon CJ, Eggebrecht AT, Todorov A, Wolff JJ, Elison JT, Adams CM, Snyder AZ, Estes AM, Zwaigenbaum L, Botteron KN, McKinstry RC, Marrus N, Evans A, Hazlett HC, Dager SR, Paterson SJ, Pandey J, Schultz RT, Styner MA, Gerig G, Schlaggar BL, Petersen SE, Piven J, Pruett JR (2018) Restricted and repetitive behavior and brain functional connectivity in infants at risk for develo** autism spectrum disorder. Biol Psychiatr: Cognit Neurosci Neuroimaging, 1–12. https://doi.org/10.1016/j.bpsc.2018.09.008
Menon V (2011) Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cognit Sci 15:483–506
Murphy K, Fox MD (2017) Towards a consensus regarding global signal regression for resting state functional connectivity MRI. NeuroImage 154(November 2016), 169–173. https://doi.org/10.1016/j.neuroimage.2016.11.052
Nair A, Keown CL, Datko M, Shih P, Keehn B, Müller RA (2014) Impact of methodological variables on functional connectivity findings in autism spectrum disorders. Hum Brain Mapp 35(8):4035–4048. https://doi.org/10.1002/hbm.22456
Nebel MB, Eloyan A, Barber AD, Mostofsky SH (2014) Precentral gyrus functional connectivity signatures of autism. Front Syst Neurosci 8(May):80. https://doi.org/10.3389/fnsys.2014.00080
Nebel MB, Eloyan A, Nettles CA, Sweeney KL, Ament K, Ward RE, Choe AS, Barber AD, Pekar JJ, Mostofsky SH (2016) Intrinsic visual-motor synchrony correlates with social deficits in autism. Biol Psychiatr 79(8):633–641. https://doi.org/10.1016/j.biopsych.2015.08.029
Padmanabhan A, Lynch CJ, Schaer M, Menon V (2017) Review the default mode network in autism. Biol Psychiatr Cogn Neurosci Neuroimaging. 2(6):476–486. https://doi.org/10.1016/j.bpsc.2017.04.004
Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. NeuroImage 52(3):1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003
Rutter M, Dilavore PC, Risi S, Gotham K, Bishop S (2012) Autism diagnostic observation schedule: ADOS-2. Western Psychological Services, Torrance
Schäfer CB, Morgan BR, Ye AX, Taylor MJ, Doesburg SM (2014) Oscillations, networks, and their development: MEG connectivity changes with age. Hum Brain Mapp 5261(February):5249–5261. https://doi.org/10.1002/hbm.22547
Uddin LQ, Supekar K, Lynch CJ, Khouzam A, Phillips J, Feinstein C, Ryali S, Menon V (2013) Salience network-based classification and prediction of symptom severity in children with autism. JAMA Psychiatr 70(8):869–879. https://doi.org/10.1001/jamapsychiatry.2013.104
Vasa RA, Mostofsky SH, Ewen JB (2016) The disrupted connectivity hypothesis of autism spectrum disorders: time for the next phase in research. Biol Psychiat Cogn Neurosci Neuroimaging 1(3):245–252. https://doi.org/10.1016/j.bpsc.2016.02.003
Verly M, Verhoeven J, Zink I, Mantini D, Van Oudenhove L, Lagae L, Sunaert S, Rommel N (2014a) Structural and functional underconnectivity as a negative predictor for language in autism. Hum Brain Mapp 35(8):3602–3615. https://doi.org/10.1002/hbm.22424
Verly M, Verhoeven J, Zink I, Mantini D, Peeters R, Deprez S, Emsell L, Boets B, Noens I, Steyaert J, Lagae L, De Cock P, Rommel N, Sunaert S (2014b) Altered functional connectivity of the language network in ASD: role of classical language areas and cerebellum. NeuroImage Clin 4:374–382. https://doi.org/10.1016/j.nicl.2014.01.008
Vissers ME, Cohen MX, Geurts HM (2012) Brain connectivity and high functioning autism: a promising path of research that needs refined models, methodological convergence, and stronger behavioral links. Neurosci Biobehav Rev 36(1):604–625. https://doi.org/10.1016/j.neubiorev.2011.09.003
Washington SD, Gordon EM, Brar J, Warburton S, Sawyer T, Wolfe A, Mease-Ference ER, Girton L, Hailu A, Mbwana J, Gaillard WD, Kalbfleisch ML, Vanmeter JW (2014) Dysmaturation of the Default Mode Network in Autism. Hum Brain Mapp 35(4):1284–1296. https://doi.org/10.1002/hbm.22252.Dysmaturation
Wechsler D (2002) Wechsler Abbreviated Scales of Intelligence. Psychological Corporation, San Antonio
Zöller D, Schaer M, Scariati E, Padula MC, Eliez S, Van De Ville D (2017) Disentangling resting-state BOLD variability and PCC functional connectivity in 22q11.2 deletion syndrome. NeuroImage 149(January):85–97. https://doi.org/10.1016/j.neuroimage.2017.01.064
Zöller D, Padula MC, Sandini C, Schneider M, Scariati E, Van De Ville D, Schaer M, Eliez S (2018) Psychotic symptoms influence the development of anterior cingulate BOLD variability in 22q11.2 deletion syndrome. Schizophr Res 193:319–328. https://doi.org/10.1016/j.schres.2017.08.003
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Morgan, B.R., Ibrahim, G.M., Vogan, V.M. et al. Characterization of Autism Spectrum Disorder across the Age Span by Intrinsic Network Patterns. Brain Topogr 32, 461–471 (2019). https://doi.org/10.1007/s10548-019-00697-w
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DOI: https://doi.org/10.1007/s10548-019-00697-w