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Language Networks in Autism Spectrum Disorder: A systematic review of connectivity-based fMRI studies

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Abstract

Autism Spectrum Disorder (ASD) is a heterogeneous condition associated with differences in functional neural connectivity relative to neurotypical (NT) peers. Language-based functional connectivity represents an ideal context in which to characterize connectivity because language is heterogeneous and linked to core features in ASD, and NT language networks are well-defined. We conducted a systematic review of language-related functional connectivity literature on individuals with ASD using PubMed, PsychInfo, Scopus, ProQuest, and Google Scholar, yielding 96 studies. Language-task studies indicated local over-connectivity within the language network and global under-connectivity of language with out-of-network regions in ASD. Resting-state studies showed mixed patterns, and connectivity was associated ASD symptomology and language skills. This evidence indicates language-task elicited local over-connectivity and global under-connectivity in ASD, but not a local versus global distinction of resting-state language-related connectivity. Associations with behavior suggest that local over-connectivity and global under-connectivity characterize ASD, and heightened language-related connectivity may support social function.

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Abbreviations

Functional connectivity:

Brain activity that shows a statistical relationship between two or more brain regions over time.

Over-connectivity:

Relatively greater strength of connectivity in ASD versus NT group

Under-connectivity:

Relatively lesser strength of connectivity in ASD versus NT group

ASD:

Autism Spectrum Disorder

NT:

Neurotypical

ROI:

Region of Interest

ADOS:

Autism Diagnostic Observation Schedule

Soc:

Socialization subscale

Comm:

Communication subscale

ADI:

Autism Diagnostic Interview

SRS:

Social Responsiveness Scale

AQ:

Autism Quotient

CELF:

Clinical Evaluation of Language Fundamentals, a standardized structural language assessment

Cortical:

Cerebral regions in the frontal, temporal, occipital, and parietal lobes

Subcortical:

Deep gray matter regions including the hippocampus, amygdala, thalamus, and putamen

Striatum:

Caudate, putamen, and ventral nuclei

p:

Posterior

a:

Anterior

v:

Ventral

m:

Medial

IFG:

Inferior frontal gyrus, including pars opercularis, pars orbitalis, and pars triangularis; represents a set of regions classically referred to as Broca’s area.

STG:

Superior temporal gyrus; the superior posterior subregion of the STG is often called Wernicke’s area; the medial subregion is often called primary auditory cortex or Heschl’s gyrus.

IPL:

Inferior parietal lobule; represents a region relevant to Wernicke’s area.

SPL:

Superior parietal lobule

TPJ:

Temporoparietal junction; represents a region relevant to Wernicke’s area.

AG:

Angular gyrus; represents a region relevant to Wernicke’s area.

MTG:

Middle temporal gyrus

DMN:

Default mode network, a task-negative network with the posterior cingulate cortex as a central node

CC:

Cingulate cortex; part of the limbic, or subcortical, system and the posterior portion of the cingulate is a central node of the DMN

Language network:

IFG, TPJ, AG, SMG, and temporal regions

Component analysis:

Separates signals by their sources and then extracts underlying sources to identify underlying networks; includes principle and independent component analysis

Effective connectivity:

tests a priori directional relationships between variables, adding paths until a best-fit model is found; includes structural equation modeling in a data-driven approach using Group Iterative Multiple Models Estimation and multivariate autoregressive modeling to estimate causal relationships.

Graph theory:

models of networks that involve a set of nodes which are interconnected by edges, such as brain regions representing nodes and functional connectivity at a given statistical threshold representing edges; specific measures may include degree centrality (a node’s number of edges), betweenness centrality (how often a node is the shortest path between two other nodes), eigenvector centrality (nodal influence within a graph/network), and small worldness (quantifies number of short-range relative to long-range edges).

References

*Articles included in review

  • *Abrams, D. A., Lynch, C. J., Cheng, K. M., Phillips, J., Supekar, K., Ryali, S., Uddin, L. Q., & Menon, V. (2013). Underconnectivity between voice-selective cortex and reward circuitry in children with autism. PNAS Proceedings of the National Academy of Sciences of the United States of America, 110(29), 12060–12065.

  • *Aija, K., Aapo, H., Leena, M., Eeva, L., Tuula, H., Ebeling, H., Vesa, K., Kiviniemi, V. J., & Soile, L. (2020). Processing of pragmatic communication in ASD: A video-based brain imaging study. Scientific Reports, 10, 21739. https://doi.org/10.1038/s41598-020-78874-2

    Article  Google Scholar 

  • *Alaerts, K., Geerlings, F., Herremans, L., Swinnen, S. P., Verhoeven, J., Sunaert, S., & Wenderoth, N. (2015). Functional organization of the action observation network in autism: A graph theory approach. PLoS One, 10(8). https://doi.org/10.1371/journal.pone.0137020

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders-Fifth Edition. American Psychiatric Association.

  • *Anderson, J. S., Nielsen, J. A., Froehlich, A. L., DuBray, M. B., Druzgal, T. J., Cariello, A. N., Cooperrider, J. R., Zielinski, B. A., Ravichandran, C., Fletcher, P. T., Alexander, A. L., Bigler, E. D., Lange, N., & Lainhart, J. E. (2011). Functional connectivity magnetic resonance imaging classification of autism. Brain: A Journal of Neurology, 134(12), 3739–3751.

  • *Anteraper, S. A., Guell, X., D’Mello, A., Joshi, N., Whitfield-Gabrieli, S., & Joshi, G. (2019). Disrupted Cerebrocerebellar Intrinsic Functional Connectivity in Young Adults with High-Functioning Autism Spectrum Disorder: A Data-Driven, Whole-Brain, High-Temporal Resolution Functional Magnetic Resonance Imaging Study. Brain Connectivity, 9(1), 48–59. https://pubmed.ncbi.nlm.nih.gov/29896995/.

  • *Balsters, J. H., Mantini, D., Apps, M. A. J., Eickhoff, S. B., & Wenderoth, N. (2016). Connectivity-based parcellation increases network detection sensitivity in resting state fMRI: An investigation into the cingulate cortex in autism. NeuroImage. Clinical, 11, 494–507. https://pubmed.ncbi.nlm.nih.gov/27114898/.

  • *Balsters, J. H., Mantini, D., & Wenderoth, N. (2018). Connectivity-based parcellation reveals distinct cortico-striatal connectivity fingerprints in Autism Spectrum Disorder. NeuroImage, 170, 412–423. https://pubmed.ncbi.nlm.nih.gov/28188914/.

  • Barendse, E. M., Schreuder, L. J., Thoonen, G., Hendriks, M. P. H., Kessels, R. P. C., Backes, W. H., Aldenkamp, A. P., & Jansen, J. F. A. (2018). Working memory network alterations in high-functioning adolescents with an autism spectrum disorder. Psychiatry and Clinical Neurosciences, 72(2), 73–83.

    Article  PubMed  Google Scholar 

  • Baudouin, S. J. (2014). Heterogeneity and convergence: The synaptic pathophysiology of autism. European Journal of Neuroscience, 39(7), 1107–1113.

    Article  PubMed  Google Scholar 

  • Baxter, L. C., Nespodzany, A., Walsh, M. J. M., Wood, E., Smith, C. J., & Braden, B. B. (2019). The influence of age and ASD on verbal fluency networks. Research in Autism Spectrum Disorders, 63, 52–62.

    Article  PubMed  PubMed Central  Google Scholar 

  • *Bednarz, H. M., Maximo, J. O., Murdaugh, D. L., O’Kelley, S., & Kana, R. K. (2017). “Decoding versus comprehension”: Brain responses underlying reading comprehension in children with autism. Brain and Language, 169, 39–47.

  • *Benkarim, O., Paquola, C., Bo-Yong, P., Seok-Jun, H., Royer, J., De Wael, R. V., Lariviere, S., Valk, S., Bzdok, D., Mottron, L., & Bernhardt, B. (2020). Functional idiosyncrasy has a shared topography with group-level connectivity alterations in autism. BioRxiv. https://doi.org/10.1101/2020.12.18.423291

  • *Bernas, A., Aldenkamp, A. P., & Zinger, S. (2018). Wavelet coherence-based classifier: A resting-state functional MRI study on neurodynamics in adolescents with high-functioning autism. Computer Methods and Programs in Biomedicine, 154, 143–151.

  • *Bhaumik, R., Pradhan, A., Das, S., & Bhaumik, D. K. (2018). Predicting Autism Spectrum Disorder Using Domain-Adaptive Cross-Site Evaluation. Neuroinformatics, 16(2), 197–205. https://pubmed.ncbi.nlm.nih.gov/29455363/.

  • Blume, J., Wittke, K., Naigles, L., & Mastergeorge, A. M. (2021). Language Growth in Young Children with Autism: Interactions Between Language Production and Social Communication. Journal of Autism and Developmental Disorders, 51(2), 644–665.

    Article  PubMed  Google Scholar 

  • *Bolton, T. A. W., Freitas, L. G. A., Jochaut, D., Jochaut, D., Giraud, A., & Van De Ville, D. (2020). Neural responses in autism during movie watching: Inter-individual response variability co-varies with symptomatology. NeuroImage, 216, 116571. https://pubmed.ncbi.nlm.nih.gov/31987996/.

  • *Bolton, T. A. W., Jochaut, D., Giraud, A., & Van De Ville, D. (2018). Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation. Human Brain Map**, 39(6), 2391–2404. https://pubmed.ncbi.nlm.nih.gov/29504186/.

  • *Braden, B. B., Smith, C. J., Thompson, A., Glaspy, T. K., Wood, E., Vatsa, D., Abbott, A. E., McGee, S. C. & Baxter, L. C. (2017). Executive function and functional and structural brain differences in middle-age adults with autism spectrum disorder. Autism Research: Official Journal of the International Society for Autism Research, 10(12), 1945–1959. https://pubmed.ncbi.nlm.nih.gov/28940848/.

  • Briggs, R. G., Conner, A. K., Baker, C. M., Burks, J. D., Glenn, C. A., Sali, G., Battiste, J. D., O’Donoghue, D. L., & Sughrue, M. E. (2018). A Connectomic Atlas of the Human Cerebrum-Chapter 18: The Connectional Anatomy of Human Brain Networks. Operative Neurosurgery, 15(1), S470–S480.

  • Buchanan, N. C. T., & Wiklund, L. O. (2021). Intersectionality Research in Psychological Science: Resisting the Tendency to Disconnect, Dilute, and Depoliticize. Research on Child and Adolescent Psychopathology, 49(1), 25–31. https://doi.org/10.1007/s10802-020-00748-y

    Article  PubMed  Google Scholar 

  • *Cardinale, R. C., Shih, P., Fishman, I., Ford, L. M., & Muller, R. (2013). Pervasive rightward asymmetry shifts of functional networks in autism spectrum disorder. JAMA Psychiatry, 70(9), 975–982. https://pubmed.ncbi.nlm.nih.gov/23903586/.

  • Carper, R. A., & Courchesne, E. (2005). Localized enlargement of the frontal cortex in early autism. Biological Psychiatry, 57, 126–133.

    Article  PubMed  Google Scholar 

  • Casanova, M. F., Buxhoeveden, D. P., Switala, A. E., & Roy, E. (2002). Minicolumnar pathology in autism. Neurology, 58, 4284–4332.

    Article  Google Scholar 

  • *Chaminade, T., Da Fonseca, D., Rosset, D., Cheng, G., & Deruelle, C. (2015). Atypical modulation of hypothalamic activity by social context in ASD. Research in Autism Spectrum Disorders, 10, 41–50.

  • *Chen, C. P.. (2014). A machine learning study of intrinsic functional connectivity in autism spectrum disorders [Unpublished Thesis]. San Diego State University.

  • *Chen, S., **ng, Y., & Kang, J. (2017). Latent and abnormal functional connectivity circuits in autism spectrum disorder. Frontiers in Neuroscience, 11(125). https://doi.org/10.3389/fnins.2017.00125

  • *Chouinard, B., Volden, J., Cribben, I., & Cummine, J. (2017). Neurological evaluation of the selection stage of metaphor comprehension in individuals with and without autism spectrum disorder. Neuroscience, 361, 19–33. https://pubmed.ncbi.nlm.nih.gov/28802915/.

  • Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2019). Cochrane handbook for systematic reviews of interventions (2nd ed.). John Wiley & Sons.

    Google Scholar 

  • Courchesne, E., Karns, C. M., Davis, H. R., Ziccardi, R., Carper, R. A., Tigue, Z. D., Chisum, H. J., Moses, P., Pierce, K., Lord, C., Lincoln, A. J., Pizzo, S., Schreibman, L., Haas, R. H., Akshoomoff, N. A., & Courchesne, R. Y. (2001). Unusual brain growth patterns in early life in patients with autistic disorder: An MRI study. Neurology, 57, 245–254.

    Article  PubMed  Google Scholar 

  • Courchesne, E., & Pierce, K. (2005). Why the frontal cortex in autism might be talking only to itself: Local over-connectivity but long-distance disconnection. Current Opinion in Neurobiology, 15(2), 225–230. https://doi.org/10.1016/j.conb.2005.03.001

    Article  PubMed  Google Scholar 

  • *Damarla, S. R., Keller, T. A., Kana, R. K., Cherkassky, V. L., Williams, D. L., Minshew, N. J., & Just, M. A. (2010). Cortical underconnectivity coupled with preserved visuospatial cognition in autism: Evidence from an fMRI study of an embedded figures task. Autism Research, 3(5), 273–279.

  • de Rubeis, S., et al. (2014). Synaptic, transcriptional, and chromatin genes disrupted in autism. Nature, 515, 209–215.

    Article  PubMed  PubMed Central  Google Scholar 

  • *Deshpande, G., Le, L., KR, S., HD, D., & RK, K. (2013). Identification of neural connectivity signatures of autism using machine learning. Frontiers in Human Neuroscience, 7, 670. https://pubmed.ncbi.nlm.nih.gov/24151458/.

  • *Deshpande, G., Libero, L. E., Sreenivasan, K. R., Deshpande, H. D., Kana, R. K. (2018). Children with ASD show links between aberrant sound processing, social symptoms, and atypical auditory interhemispheric and thalamocortical functional connectivity. Developmental Cognitive Neuroscience, 29, 117–126. https://pubmed.ncbi.nlm.nih.gov/28223033/.

  • Di Martino, A., Zuo, X. N., Kelly, C., Grzadzinski, R., Mennes, M., Schvarcz, A., Rodman, J., Lord, C., Castellanos, F. X., & Milham, M. P. (2013). Shared and distinct intrinsic functional network centrality in autism and attention-deficit/hyperactivity disorder. Biological Psychiatry, 74(8), 623–632. https://doi.org/10.1016/j.biopsych.2013.02.011

    Article  PubMed  PubMed Central  Google Scholar 

  • Di Martino, A., et al. (2014). The autism brain imaging data exchange: Towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular Psychiatry, 19(6), 659–667.

    Article  PubMed  Google Scholar 

  • *Dinstein, I., Pierce, K., Eyler, L., Solso, S., Malach, R., Behrmann, M., & Courchesne, E. (2011). Disrupted neural synchronization in toddlers with autism. In Neuron (Vol. 70, Issue 6, pp. 1218–1225). https://pubmed.ncbi.nlm.nih.gov/21689606/.

  • *Dryburgh, E., McKenna, S., & Rekik, I. (2020). Predicting full-scale and verbal intelligence scores from functional connectomic data in individuals with Autism Spectrum Disorder. Brain Imaging and Behavior, 14(5), 1769–1778.

  • Ebert, D. H., & Greenberg, M. E. (2013). Activity-dependent neuronal signaling and autism spectrum disorder. Nature, 493, 327–337.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ebrahimi-Fakhari, D., & Sahin, M. (2015). Autism and the synapse emerging mechanisms and mechanism-based therapies. Developmental Disorders, 28(2), 91–102.

    Google Scholar 

  • Eigsti, I. M., de Marchena, A. B., Schuh, J. M., & Kelley, E. (2011). Language acquisition in autism spectrum disorders: A developmental review. Research in Autism Spectrum Disorders, 5, 681–691 https://doi.org/10.1016/j.rasd.2010.09.001.

  • Eigsti, I. M., Stevens, M. C., Schultz, R. T., Barton, M., Kelley, E., Naigles, L., Orinstein, A., Troyb, E., & Fein, D. A. (2016). Language comprehension and brain function in individuals with an optimal outcome from autism. NeuroImage: Clinical, 10, 182–191.

  • *Fan, L., Booth, J. R., Liu, M., Chou, T., & Gau, S. S. (2021). Developmental differences in neural connectivity for semantic processing in youths with autism. Journal of Child Psychology and Psychiatry, 62(9), 1090–1099.

  • Fishman, I., Keown, C. L., Lincoln, A. J., Pineda, J. A., & Müller, R. A. (2014). Atypical cross talk between mentalizing and mirror neuron networks in autism spectrum disorder. JAMA Psychiatry, 71(7), 751–760.

    Article  PubMed  PubMed Central  Google Scholar 

  • *Gabrielsen, T. P., Anderson, J. S., Stephenson, K. G., Beck, J., King, J. B., Kellems, R., Top Jr., D. V., Russel, N. C. C., Anderberg, E., Lundwall, R. A., Hansen, B., & South, M. (2018). Functional MRI connectivity of children with autism and low verbal and cognitive performance. Molecular Autism, 9, 67. https://pubmed.ncbi.nlm.nih.gov/30603063/.

  • *Gao, Y. (2020). Heterogeneity of the Language Network in Autism Spectrum Disorders: A Data-Driven Study of Neurophenotypes [Unpublished Dissertation]. University of California, San Diego.

  • *Gao, Y., Linke, A., Jao Keehn, R. J., Punyamurthula, S., Jahedi, A., Gates, K., Fishman, I., & Müller, R. (2019). The language network in autism: Atypical functional connectivity with default mode and visual regions. Autism Research, 12(9), 1344–1355.

  • Girolamo, T., Parker, T. C., & Eigsti, I.-M. (2022). Incorporating dis/ability studies and critical race theory to combat systematic exclusion of black, indigenous, and people of color in clinical neuroscience. Frontiers in Neuroscience, 16, 988092. https://doi.org/10.3389/fnins.2022.988092

    Article  PubMed  PubMed Central  Google Scholar 

  • *Gotts, S. J., Simmons, W. K., Milbury, L. A., Wallace, G. L., Cox, R. W., & Martin, A. (2012). Fractionation of social brain circuits in autism spectrum disorders. Brain: A Journal of Neurology, 135(9), 2711–2725.

  • *Guo, X., Simas, T., Lai, M., Lombardo, M. V, Chakrabarti, B., Ruigrok, A. N. V, Bullmore, E. T., Baron‐Cohen, S., Chen, H., & Suckling, J. (2019). Enhancement of indirect functional connections with shortest path length in the adult autistic brain. Human Brain Map**, 40(18), 5354–5369.

  • Happe, F., & Frith, U. (2006). The weak coherence account; Detail-focused cognitive style in autism spectrum disorders. Journal of Autism and Developmental Disorders, 36, 5–25.

    Article  PubMed  Google Scholar 

  • *Hegarty II, J. P. (2015). Network coherence in autism spectrum disorder: A multimodal neuroimaging study of functional connectivity and spectroscopy MRI [Unpublished Dissertation]. University of Missouri – Columbia.

  • Herringshaw, A. J., Ammons, C. J., DeRamus, T. P., & Kana, R. K. (2016). Hemispheric differences in language processing in autism spectrum disorders: A meta-analysis of neuroimaging studies. Autism Research, 9(10), 1046–1057. https://doi.org/10.1002/aur.1599

    Article  PubMed  Google Scholar 

  • Hong, S.-J., Hyung, B., Paquola, C., & Bernhardt, B. C. (2019). The superficial white matter in autism and its role in connectivity anomalies and symptom severity. Cerebral Cortex, 29(10), 4415–4425. https://doi.org/10.1093/cercor/bhy321

    Article  PubMed  Google Scholar 

  • Horwitz, B., Rumsey, J. M., Grady, C. L., & Rapoport, S. I. (1988). The cerebral metabolic landscape in autism. Intercorrelations of regional glucose utilization. Archives of Neurology, 45, 749–755.

    Article  PubMed  Google Scholar 

  • *Ingalhalikar, M., Shinde, S., Karmarkar, A., Rajan, A., Rangaprakash, D., & Deshpande, G. (2021). Functional connectivity-based prediction of Autism on site harmonized ABIDE dataset. IEEE Transactions on Bio-Medical Engineering. https://pubmed.ncbi.nlm.nih.gov/33989150/.

  • Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. The American Journal of Psychiatry, 167(7), 748–751. https://doi.org/10.1176/appi.ajp.2010.09091379

    Article  PubMed  Google Scholar 

  • *Itahashi, T., Yamada, T., Watanabe, H., Nakamura, M., Jimbo, D., Shioda, S., Toriizuka, K., Kato, N., & Hashimoto, R. (2014).Altered network topologies and hub organization in adults with autism: a resting-state fMRI study. PloS One, 9(4), e94115.

  • *Ivin, G., Heasman, M., Pretzsch, E., Williams, S., Murpjy, D. G. M., Daly, E., & McAlonan, G. M. (2021). Modulation of striatal functional connectivity differences in adults with and without autism spectrum disorder in a single-dose randomized trial of cannabidivarin. Molecular Autism, 12(1), 49. https://pubmed.ncbi.nlm.nih.gov/34210360/.

  • *Jasmin, K., Gotts, S. J., Xu, Y., Liu, S., Riddle, C. D., Ingeholm, J. E., Kenworthy, L., Wallace, G. L., Braun, A. R., & Martin, A. (2019). Overt social interaction and resting state in young adult males with autism: core and contextual neural features. Brain: A Journal of Neurology, 142(3), 808–822. https://pubmed.ncbi.nlm.nih.gov/30698656/.

  • *Jones, T. B., Bandettini, P. A., Kenworthy, L., Case, L. K., Milleville, S. C., Martin, A., & Birn, R. M. (2010). Sources of group differences in functional connectivity: An investigation applied to autism spectrum disorder. NeuroImage, 49(1), 401–414.

  • Jones, D. R., & Mandell, D. S. (2020). To address racial disparities in autism research, we must think globally, act locally. Autism, 24(7), 1587–1589. https://doi.org/10.1177/1362361320948313

    Article  PubMed  Google Scholar 

  • *Joshi, G., Arnold Anteraper, S., Patil, K. R., Semwal, M., Goldin, R. L., Furtak, S. L., Chai, X. J., Saygin, Z. M., Gabrieli, J. D. E., & Biederman, J. (2017). Integration and segregation of default mode network resting-state functional connectivity in transition-age males with high-functioning autism spectrum disorder: a proof-of-concept study. Brain Connectivity, 7(9), 558–573.

  • Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., & Minshew, N. J. (2007). Functional and anatomical cortical underconnectivity in autism: Evidence from an fmri study of an executive function task and corpus callosum morphometry. Cerebral Cortex, 17(4), 951–961.

    Article  PubMed  Google Scholar 

  • *Just, M. A., Cherkassky, V. L., Keller, T. A., & Minshew, N. J. (2004). Cortical activation and synchronization during sentence comprehension in high-functioning autism: Evidence of underconnectivity. Brain: A Journal of Neurology, 127(8), 1811–1821.

  • *Kaku, S. M., Jayashankar, A., Girimaji, S. C., Bansal, S., Gohel, S., Bharath, R. D., & Srinath, S. (2019). Early childhood network alterations in severe autism. Asian Journal of Psychiatry, 39, 114–119.

  • *Kaminer, I. E.. (2021). Language Network Differences among Verbally Fluent Autistic Adults: A Comparison with Neurotypical Peers [Unpublished Thesis]. Drexel University.

  • *Kana, R. K., Keller, T. A., Cherkassky, V. L., Minshew, N. J., & Just, M. A. (2006). Sentence comprehension in autism: Thinking in pictures with decreased functional connectivity. Brain: A Journal of Neurology, 129(9), 2484–2493.

  • Kana, R. K., Keller, T. A., Minshew, N. J., & Just, M. A. (2007). Inhibitory control in high functioning autism: Decreased activation and underconnectivity in inhibition networks. Biological Psychiatry, 62(3), 198–206.

    Article  PubMed  Google Scholar 

  • *Kana, R. K., Sartin, E. B., Stevens, C. J., Deshpande, H. D., Klein, C., Klinger, M. R., & Klinger, L. G. (2017). Neural networks underlying language and social cognition during self-other processing in Autism spectrum disorders. Neuropsychologia, 102, 116–123.

  • *Karten, A., & Hirsch, J. (2015). Brief report: Anomalous neural deactivations and functional connectivity during receptive language in autism spectrum disorder: A functional MRI study. Journal of Autism and Developmental Disorders, 45(6), 1905–1914.

  • *Kazeminejad, A. (2019). Using Brain Topological Features Extracted from Resting State fMRI to Classify Autism Spectrum Disorder [Unpublished Thesis]. Schulich School of Engineering.

  • Keown, C. L., Datko, M. C., Chen, C. P., Maximo, J. O., Jahedi, A., & Muller, R. (2017). Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2(1), 66–75.

    PubMed  Google Scholar 

  • Kjelgaard, M. M., & Tager-Flusberg, H. (2001). An investigation of language impairment in autism: Implications for genetic subgroups. Language and Cognitive Processes, 16(2–3), 287–308. https://doi.org/10.1080/01690960042000058

    Article  PubMed  PubMed Central  Google Scholar 

  • *Koshino, H., Carpenter, P. A., Minshew, N. J., Cherkassky, V. L., Keller, T. A., & Just, M. A. (2005). Functional connectivity in an fMRI working memory task in high-functioning autism. In NeuroImage, 24(3), pp. 810–821.

  • *Koshino, H., Kana, R. K., Keller, T. A., Cherkassky, V. L., Minshew, N. J., & Just, M. A. (2008). fMRI investigation of working memory for faces in autism: Visual coding and underconnectivity with frontal areas. Cerebral Cortex, 18(2), 289–300.

  • Kuhl, P. K. (2021). Language. In E. R. Kandel, J. D. Koester, S. H. Mack, & S. A. Siegelbaum (Eds.), Principles of Neural Science (6th ed., pp. 1370–1391). McGraw Hill.

    Google Scholar 

  • *Lai, G. Y. (2011). Functional and Structural Neurocircuitry of Language and Music Systems in Autism Spectrum Disorder [Unpublished Dissertation]. Columbia University.

  • Lanz, T. A., Guilmette, E., Gorsink, M. M., Fischer, J. E., Fitzgerald, L. W., Stephenson, D. T., & Pletcher, M. T. (2013). Transcriptomic analysis of genetically defined autism candidate genes reveals common mechanisms of action. Molecular Autism, 4(45), 1–17.

    Google Scholar 

  • Larson, C., Rivera-Figueroa, K., Thomas, H. R., Fein, D., Stevens, M. C., & Eigsti, I. (2022). Structural language impairment in Autism Spectrum Disorder versus Loss of Autism Diagnosis: Behavioral and neural characteristics. NeuroImage: Clinical, 34, 103043.

  • *Lee, Y., Park, B., James, O., Kim, S.., & Park, H. (2017). Autism Spectrum Disorder Related Functional Connectivity Changes in the Language Network in Children, Adolescents and Adults. Frontiers in Human Neuroscience, 11, 418. https://pubmed.ncbi.nlm.nih.gov/28867997/.

  • *Lee, P. S., Yerys, B. E., Della Rosa, A., Foss-Feig, J., Barnes, K. A., James, J. D., Vanmeter, J., Vaidya, C. J., Gaillard, W. D., & Kenworthy, L. E. (2009). Functional connectivity of the inferior frontal cortex changes with age in children with autism spectrum disorders: A fcMRI study of response inhibition. Cerebral Cortex, 19(8), 1787–1794.

  • *Levinson, H. J. (2021). The Neural Representation of Abstract Concepts in Typical and Atypical Cognition [Unpublished Dissertation]. Rutgers The State University of New Jersey, Graduate School – Newark.

  • *Li, Q., Becker, B., Jiang, X., Zhao, Z., Zhang, Q., Yao, S., & Kendrick, K. M. (2019). Decreased interhemispheric functional connectivity rather than corpus callosum volume as a potential biomarker for autism spectrum disorder. Cortex; A Journal Devoted to the Study of the Nervous System and Behavior, 119, 258–266. https://pubmed.ncbi.nlm.nih.gov/31167156/.

  • *Liang, D., **a, S., Zhang, X., & Zhang, W. (2021). Analysis of brain functional connectivity neural circuits in children with autism based on persistent homology. Frontiers in Human Neuroscience, 15, 745671. https://doi.org/10.3389/fnhum.2021.745671

    Article  PubMed  PubMed Central  Google Scholar 

  • *Linke, A. C., Keehn, R. J. J., Pueschel, E. B., Fishman, I., & Müller, R. (2018). Developmental Cognitive Neuroscience Children with ASD show links between aberrant sound processing , social symptoms , and atypical auditory interhemispheric and thalamocortical functional connectivity. Accident Analysis and Prevention, 29, 117–126.https://doi.org/10.1016/j.dcn.2017.01.007.

  • *Libero, L. E., Stevens Jr, C. E., & Kana, R. K. (2014). Attribution of emotions to body postures: An independent component analysis study of functional connectivity in autism. Human Brain Map**, 35(10), 5204–5218.

  • *Lombardo, M. V., Eyler, L., Moore, A., Datko, M., Cynthia, C. B., Cha, D., Courchesne, E., & Pierce, K. (2019). Default mode-visual network hypoconnectivity in an autism subtype with pronounced social visual engagement difficulties. ELife, 8(e47427). https://doi.org/10.7554/eLife.47427

  • *Lombardo, M. V, Pramparo, T., Gazestani, V., Warrier, V., Bethlehem, R. A. I., Barnes, C. C., Lopez, L., Lewis, N. E., Eyler, L., Pierce, K., & Courchesne, E. (2018). Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes. Nature Neuroscience, 21(12), 1680–1688.

  • Lugnegård, T., Hallerbäck, M. U., & Gillberg, C. (2011). Psychiatric comorbidity in young adults with a clinical diagnosis of Asperger syndrome. Research in Developmental Disabilities, 32(5), 1910–1917. https://doi.org/10.1016/j.ridd.2011.03.025

    Article  PubMed  Google Scholar 

  • *Mash, L. E., Linke, A. C., Gao, Y., Wilkinson, M., Olson, M. A., Keehn, R. J. J., & Muller, R.. (2021). Blood Oxygen Level-Dependent Lag Patterns Differ Between Rest and Task Conditions, but Are Largely Typical in Autism. Brain Connectivity. https://pubmed.ncbi.nlm.nih.gov/34102876/.

  • *Mason, R. A., Williams, D. L., Kana, R. K., Minshew, N., & Just, M. A. (2008). Theory of Mind disruption and recruitment of the right hemisphere during narrative comprehension in autism. Neuropsychologia, 46(1), 269–280.

  • *Masson, H. L., de Beeck, H. O., & Boets, B. (2020). Reduced task-dependent modulation of functional network architecture for positive versus negative affective touch processing in autism spectrum disorders. NeuroImage, 219, 117009. https://pubmed.ncbi.nlm.nih.gov/32504816/.

  • *Maximo, J. O. (2016). Changes in intrinsic local functional connectivity in children with autism followed by a visualizing/verbalizing reading intervention [Unpublished Thesis]. The University of Alabama at Birmingham.

  • Maximo, J. O., Murdaugh, D. L., O’Kelley, S., & Kana, R. K. (2017). Changes in intrinsic local connectivity after reading intervention in children with autism. Brain and Language, 175, 11–17.

    Article  PubMed  Google Scholar 

  • *Mizuno, A., Liu, Y., Williams, D. L., Keller, T. A., Minshew, N. J., & Just, M. A. (2011). The neural basis of deictic shifting in linguistic perspective-taking in high-functioning autism. Brain: A Journal of Neurology, 134(8), 2422–2435.

  • Müller, R. A., Shih, P., Keehn, B., Deyoe, J. R., Leyden, K. M., & Shukla, D. K. (2011). Underconnected, but how? A survey of functional connectivity MRI studies in autism spectrum disorders. Cerebral Cortex, 21(10), 2233–2243.

    Article  PubMed  PubMed Central  Google Scholar 

  • Murdaugh, D. L., Deshpande, H. D., & Kana, R. K. (2016). The impact of reading intervention on brain responses underlying language in children with autism. Autism Research, 9(1), 141–154.

    Article  PubMed  Google Scholar 

  • Murdaugh, D. L., Maximo, J. O., & Kana, R. K. (2015). Changes in intrinsic connectivity of the brain’s reading network following intervention in children with autism. Human Brain Map**, 36(8), 2965–2979.

    Article  PubMed  PubMed Central  Google Scholar 

  • *Murdaugh, D. L., Shinkareva, S. V., Deshpande, H. R., Wang, J., Pennick, M. R., & Kana, R. J. (2012). Differential deactivation during mentalizing and classification of autism based on default mode network connectivity. PloS One, 7(11), e50064. https://pubmed.ncbi.nlm.nih.gov/23185536/.

  • *Nair, S.. (2016). Links between local and long distance connectivity in autism spectrum disorder [Unpublished Thesis]. San Diego State University.

  • Nair, A. (2015). The role of thalamocortical networks in the symptomatology of autism spectrum disorders [Unpublished Dissertation]. University of California.

    Google Scholar 

  • Narayanan, A., White, C. A., Saklayen, S., Scaduto, M. J., Carpenter, A. L., Abduljalil, A., Schmalbrock, P., & Beversdorf, D. Q. (2010). Effect of propranolol on functional connectivity in autism spectrum disorder—A pilot study. Brain Imaging and Behavior, 4(2), 189–197.

    Article  PubMed  PubMed Central  Google Scholar 

  • Nebel, M. B., Joel, S. E., Muschelli, J., Barber, A. D., Caffo, B. S., Pekar, J. J., & Mostofsky, S. H. (2012). Disruption of functional organization within the primary motor cortex in children with autism. Human Brain Map**, 35(2), 567–580.

    Article  PubMed  PubMed Central  Google Scholar 

  • *Nielsen, J. A. (2013). Brain functional magnetic resonance imaging lateralization and diagnostic classification in autism [Unpublished Dissertation]. The University of Utah.

  • *Nielsen, J. A., Zielinski, B. A., Fletcher, P. T., Alexander, A. L., Lange, N., Bigler, E. D., Lainhart, J. E., & Anderson, J. S. (2013). Multisite functional connectivity MRI classification of autism: ABIDE results. Frontiers in Human Neuroscience, 7, 599. https://pubmed.ncbi.nlm.nih.gov/24093016/.

  • *Nielsen, J. A., Zielinski, B. A., Fletcher, P. T., Alexander, A. L., Lange, N., Bigler, E. D., Lainhart, J. E., Anderson, J. S. (2014). Abnormal lateralization of functional connectivity between language and default mode regions in autism. Molecular Autism, 5(1), 8. https://pubmed.ncbi.nlm.nih.gov/24502324/.

  • Odriozola, P., Uddin, L. Q., Lynch, C. J., Kochalka, J., Chen, T., & Menon, V. (2016). Insula response and connectivity during social and non-social attention in children with autism. Social Cognitive and Affective Neuroscience, 11(3), 433–444.

    Article  PubMed  Google Scholar 

  • Olulade, O. A., Seydell-Greenwald, A., Chambers, C. E., Turkeltaub, P. E., Dromerick, A. W., Berl, M. M., Gaillard, W. D., & Newport, E. L. (2020). The neural basis of language development: Changes in lateralization over age. Proceedings of the National Academy of Sciences of the United States of America, 117(38), 23477–23483. https://doi.org/10.1073/pnas.1905590117

    Article  PubMed  PubMed Central  Google Scholar 

  • Paakki, J., Rahko, J., Long, X., Moilanen, I., Tervonen, O., Nikkinen, J., Starck, T., Remes, J., Hurtig, T., Haapsamo, H., Jussila, K., Kuusikko-Gauffin, S., Mattila, M., Zang, Y., & Kiviniemi, V. (2010). Alterations in regional homogeneity of resting-state brain activity in autism spectrum disorders. Brain Research, 1321, 169–179.

    Article  PubMed  Google Scholar 

  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(71). https://doi.org/10.1136/bmj.n71

  • Pantelis, P. C., Byrge, L., Tyszka, J. M., Adolphs, R., & Kennedy, D. P. (2015). A specific hypoactivation of right temporo-parietal junction/posterior superior temporal sulcus in response to socially awkward situations in autism. Social Cognitive and Affective Neuroscience, 10(10), 1348–1356.

    Article  PubMed  PubMed Central  Google Scholar 

  • *Pereira Quezada, J. A.. (2019). Real-Time Neurofeedback Based on Functional Magnetic Resonance Imaging as a New Approach to Study the Face Processing Network in Autism Spectrum [Unpublished Dissertation]. Pontificia Universidad Catolica de Chile.

  • Pierce, K., Haist, F., Sedaghat, F., & Courchesne, E. (2010). The brain response to personally familiar faces in autism: Findings of fusiform activity and beyond. Brain, 127(12), 2703–2716.

    Article  Google Scholar 

  • *Pines, A. R., Sussman, B., Wyckoff, S. N., McCarty, P. J., Bunch, R., Frye, R. E., & Boerwinkle, V. L. (2021). Locked-in Intact Functional Networks in Children with Autism Spectrum Disorder: A Case-Control Study. Journal of Personalized Medicine, 11(9), 854.

  • Price, C. J. (2010). The anatomy of language: A review of 100 fMRI studies published in 2009. Annals of the New York Academy of Sciences, 1191, 62–88.

    Article  PubMed  Google Scholar 

  • *Pretzsch, C.M., Floris, D.L., Voinescu, B., Elsahib, M., Mendez, M.A., Wichers, R., Ajram, L., Ivin, G., Heasman, M., Pretzsch, E., Williams, S., Murphy, D.G.M., Daly, E., & McAlonan, G.M. (2021). Modulation of striatal functional connectivity differences in adults with and without autism spectrum disorder in a single-dose randomized trial of cannabidivarin. Molecular autism, 12(1). https://doi.org/10.1186/s13229-021-00454-6.

  • Rausch, A., Zhang, W., Haak, K. V., Mennes, M., Hermans, E. J., van Oort, E., van Wingen, G., Beckmann, C. F., Buitelaar, J. K., & Groen, W. B. (2016). Altered functional connectivity of the amygdaloid input nuclei in adolescents and young adults with autism spectrum disorder: A resting state fMRI study. Molecular Autism, 7(13). https://doi.org/10.1186/s13229-015-0060-x

  • *Redcay, E., Moran, J. M., Mavros, P. L., Tager-Flusberg, H., Gabrieli, J. D. E., & Whitfield-Gabrieli, S. (2013). Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder. Frontiers in Human Neuroscience, 7(573). https://doi.org/10.3389/fnhum.2013.00573

  • Rudie, J. D. (2012). Imaging Genetics of Functional and Structural Connectivity in Children with Autism [Unpublished Dissertation]. University of California.

    Google Scholar 

  • Sahin, M., & Sur, M. (2015). Genes, circuits, and precision therapies for autism and related neurodevelopmental disorders. Science, 350(6263). https://doi.org/10.1126/science.aab3897

  • *Sandhya, C., Vidhusha, S., Gayathri, R. S., Sneha Priya, B., & Kavitha, A. (2015). Assessment of functional connectivity in autistic brain fMRI. Proceedings of 2015 IEEE 14th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2015 (pp. 169–174). https://doi.org/10.1109/ICCI-CC.2015.7259382

  • *Sariya, Y. K., & Anand, R. S. (2016). Assessment of social and cognitive dysfunction of autism spectrum disorder through functional network connectivity. In 2016 IEEE Annual India Conference (INDICON 2016) (1–4). https://doi.org/10.1109/INDICON.2016.7839061

  • *Seok-Jun, H., Mottron, L., Bo-Yong, P., Benkarim, O., Valk, S. L., Paquola, C., Larivière, S., De Wael, R. V., Degré-Pelletier, J., Soulieres, I., Ramphal, B., Margolis, A., Milham, M., Di Martino, A., & Bernhardt, B. C. (2021). A convergent structure-function substrate of cognitive imbalances in autism. BioRxiv. https://doi.org/10.1093/cercor/bhac156

  • *Sharda, M., Midha, R., Malik, S., Mukerji, S., & Singh, N. C. (2015). Fronto‐temporal connectivity is preserved during sung but not spoken word listening, across the autism spectrum. Autism Research, 8(2), 174–186.

  • *Shen, M. D., Li, D. D., Keown, C. L., Lee, A., Johnson, R. T., Angkustsiri, K., Rogers, S. J., Müller, R.-A., Amaral, D. G., & Nordahl, C. W. (2016). Functional connectivity of the amygdala is disrupted in preschool-aged children with autism spectrum disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 55(9), 817–824.

  • *Shen, M. D., Shih, P., Öttl, B., Keehn, B., Leyden, M. S., Gaffrey, M. S., & Muller, R. (2012). Atypical lexicosemantic function of extrastriate cortex in autism spectrum disorder: evidence from functional and effective connectivity. NeuroImage, 62(3), 1780–1791. https://pubmed.ncbi.nlm.nih.gov/22699044/.

  • *Shi, C., Zhang, J., & Wu, X. (2020). An fMRI Feature Selection Method Based on a Minimum Spanning Tree for Identifying Patients with Autism. (2020). Symmetry, 12(12), 1995.

  • *Shih, P., Keehn, B., Oram, J. K., Leyden, K. M., Keown, C. L., & Müller, R.-A. (2011). Functional differentiation of posterior superior temporal sulcus in autism: A functional connectivity magnetic resonance imaging study. Biological Psychiatry, 70(3), 270–277.

  • Shukla, D. K., Keehn, B., & Muller, R. A. (2010). Regional homogeneity of fMRI times series in autism spectrum disorders. Neuroscience Letters, 476(1), 46–51.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sporns, O., Chialvo, D. R., Kaiser, M., & Hilgetag, C. C. (2004). Organization, development and function of complex brain networks. Trends in Cognitive Science, 8, 418–425.

    Article  Google Scholar 

  • *Sridhar, A. (2021). Reconfiguration of Neural Networks in Adolescents with ASD During Lexical Decision [Unpublished Thesis]. San Diego State University.

  • *Sridhar, A., Keehn, R., Jao, J., Wilkinson, M., Gao, Y., Olson, M., Mash, L. E., Alemu, K., Manley, A., Marinkovic, K., Linke, A., & Müller, R.-A. (2021). Increased heterogeneity and task-related reconfiguration of functional connectivity within a lexicosemantic network in autism. 1–50. https://doi.org/10.1101/2021.11.22.469604v1

  • *Srinivasan, V., Udayakumar, N., & Anandan, K. (2020). Influence of Primary Auditory Cortex in the Characterization of Autism Spectrum in Young Adults using Brain Connectivity Parameters and Deep Belief Networks: An fMRI Study. Current Medical Imaging, 16(9), 1059–1073. https://pubmed.ncbi.nlm.nih.gov/33342398/.

  • Stevens, M. C. (2016). The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation. Neuroscience and Biobehavioral Reviews, 70, 13–32. https://doi.org/10.1016/j.neubiorev.2016.07.027

    Article  PubMed  Google Scholar 

  • *Urchs, S. G., Tam, A., Orban, P., Moreau, C., Benhajali, Y., Nguyen, H. D., Evans, A. C., & Bellec, P. (2020). Subtypes of functional connectivity associate robustly with ASD diagnosis. BioRxiv. https://doi.org/10.1101/2020.04.14.040576

  • Vargas, D. L., Nascimbene, C., Krishnan, C., Zimmerman, A. W., & Pardo, C. A. (2005). Neuroglial activation and neuroinflammation in the brain of patients with autism. Annals of Neurology, 57, 67–81.

    Article  PubMed  Google Scholar 

  • Vasa, R. A., Mostofsky, S. H., & Ewen, J. B. (2016). The Disrupted Connectivity Hypothesis of Autism Spectrum Disorders: Time for the Next Phase in Research. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 1(3), 245–252.

    PubMed  Google Scholar 

  • *Venkataraman, A., Duncan, J. S., Yang, D. Y. J, & Pelphrey, K. A. (2015). An unbiased Bayesian approach to functional connectomics implicates social-communication networks in autism. NeuroImage. Clinical, 8, 356–366. https://pubmed.ncbi.nlm.nih.gov/26106561/.

  • *Verly, M., Verhoeven, J., Zink, I., Mantini, D., Van Oudenhove, L., Lagae, L., Sunaert, S., & Rommel, N. (2014). Structural and functional underconnectivity as a negative predictor for language in autism. Human Brain Map**, 35(8), 3602–3615.

  • Vértes, P. E., & Bullmore, E. T. (2015). Annual research review: Growth connectomics - The organization and reorganization of brain networks during normal and abnormal development. Journal of Child Psychology and Psychiatry and Allied Disciplines, 56(3), 299–320.

    Article  PubMed  Google Scholar 

  • Verly, M., et al. (2014). Altered functional connectivity of the language network in ASD: Role of classical language areas and cerebellum. NeuroImage: Clinical, 4, 374–382.

  • Vissers, M. E., X Cohen, M., & Geurts, H. M. (2012). Brain connectivity and high functioning autism: A promising path of research that needs refined models, methodological convergence, and stronger behavioral links. Neuroscience and Biobehavioral Reviews, 36(1), 604–625.

  • *Wan, B., Wang, Z., Jung, M., Lu, Y., He, H., Chen, Q., & **, Y. (2019). Effects of the Co-occurrence of Anxiety and Attention-Deficit/Hyperactivity Disorder on Intrinsic Functional Network Centrality among Children with Autism Spectrum Disorder. Autism Research: Official Journal of the International Society for Autism Research, 12(7), 1057–1068. https://pubmed.ncbi.nlm.nih.gov/31074587/.

  • Wang, Q., Li, H., Li, Y., Lv, Y., Ma, H., **ang, A., & Jia, X. (2021). Resting-state abnormalities in functional connectivity of the default mode network in autism spectrum disorder: A meta-analysis. Brain Imaging and Behavior, 15, 2583–2592.

    Article  PubMed  Google Scholar 

  • Weng, S.-J., Wiggins, J. L., Peltier, S. J., Carrasco, M., Risi, S., Lord, C., & Monk, C. S. (2010). Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders. Brain Research, 1313, 202–214.

    Article  PubMed  Google Scholar 

  • *White, S. J., Frith, U., Rellecke, J., Al-Noor, Z., & Gilbert, S. J. (2014). Autistic adolescents show atypical activation of the brain’s mentalizing system even without a prior history of mentalizing problems. Neuropsychologia, 56, 17–25. https://pubmed.ncbi.nlm.nih.gov/24361475/.

  • Wilson, T. W., Rojas, D. C., Reite, M. L., Teale, P. D., & Rogers, S. J. (2007). Children and adolescents with autism exhibit reduced MEG steady-state gamma responses. Biological Psychiatry, 62, 192–197.

    Article  PubMed  Google Scholar 

  • *Williams, D. L., Cherkassky, V. L., Mason, R. A., Keller, T. A., Minshew, N. J., & Just, M. A. (2013). Brain function differences in language processing in children and adults with autism. Autism Research, 6(4), 288–302.

  • Wilson, S. M., Yen, M., & Eriksson, D. K. (2018). An adaptive semantic matching paradigm for reliable and valid language map** in individuals with aphasia. Human Brain Map**, 39(8), 3285–3307. https://doi.org/10.1002/hbm.24077

    Article  PubMed  PubMed Central  Google Scholar 

  • Wittke, K., Mastergeorge, A. M., Ozonoff, S., Rogers, S. J., & Naigles, L. R. (2017). Grammatical language impairment in autism spectrum disorder: Exploring language phenotypes beyond standardized testing. Frontiers in Psychology, 8(APR), 1–12.

  • *Yang, M., Cao, M., Chen, Y., Chen, Y., Fan, G., Li, C., Wang, J., & Liu, T. (2021).Large-Scale Brain Functional Network Integration for Discrimination of Autism Using a 3-D Deep Learning Model. Frontiers in Human Neuroscience, 15, 277.

  • Yerys, B. E., et al. (2015). Default mode network segregation and social deficits in autism spectrum disorder: Evidence from non-medicated children DMN in children with ASD. NeuroImage: Clinical, 9, 223–232.

  • ***ao, Y., Wen, T. H., Kupis, L., Eyler, L. T., Goel, D., Lombardo, M. V, Pierce, K., & Courchesne, E. (2021). Disrupted intrinsic connectivity links to language and social deficits in toddlers with autism. BioRxiv, the preprint server for biology.

  • *Xu, J., Wang, C., Xu, Z., Li, T., Chen, F., Chen, K., Gao, J., Wang, J., & Hu, Q. (2020). Specific functional connectivity patterns of middle temporal gyrus subregions in children and adults with autism spectrum disorder. Autism Research, 13(3), 410–422.

  • *Zhao, W. (2017). Atypical intrinsic functional connectivity of the core face perception system in autism spectrum disorder [Unpublished Thesis]. San Diego State University.

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Acknowledgements

The authors are very grateful to members of the Connecticut Autism and Language Lab for their work and for our funding from the National Institutes of Health R01MH112687-01A1 and T32DC017703.

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  1. Department of Psychological Sciences, University of Connecticut, Unit 1020, 406 Babbidge Rd, Storrs, CT, 06269, USA

    Caroline Larson, Hannah R. Thomas, Jason Crutcher & Inge-Marie Eigsti

  2. CT Institute for the Brain and Cognitive Sciences, Storrs, CT, USA

    Caroline Larson & Inge-Marie Eigsti

  3. Olin Neuropsychiatry Research Center at the Institute of Living, Hartford, CT, USA

    Michael C. Stevens

  4. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

    Michael C. Stevens

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Caroline Larson: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – original and review/editing; Hannah R. Thomas: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Validation, Writing –review/editing; Jason Crutcher: Conceptualization, Formal Analysis, Investigation, Methodology, Validation, Writing –review/editing; Michael C. Stevens: Conceptualization, Investigation, Methodology, Validation, Writing – review/editing; Inge-Marie Eigsti: Conceptualization, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Visualization, Writing – review/editing.

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Larson, C., Thomas, H.R., Crutcher, J. et al. Language Networks in Autism Spectrum Disorder: A systematic review of connectivity-based fMRI studies. Rev J Autism Dev Disord (2023). https://doi.org/10.1007/s40489-023-00382-6

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