A review of the use of EEG connectivity to measure the neurological characteristics of the sensory features in young people with autism
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition affecting about 1 in 100 children and is currently incurable. ASD represents a challenge to traditional methods of assessment and diagnosis, and it has been suggested that direct measures of brain activity and connectivity between brain regions during demanding tasks represents a potential pathway to building more accurate models of underlying brain function and ASD. One of the key behavioural diagnostic indicators of ASD consists of sensory features (SF), often characterised by over- or under-reactivity to environmental stimuli. SF are associated with behavioural difficulties that impede social and education success in these children as well as anxiety and depression. This review examines the previous literature on the measurement of EEG connectivity and SF observed in individuals with ASD.
References
APA (2000). Diagnostic and Statistical Manual of Mental Disorders (4th ed, Text Revision. Washington, DC, USA: American Psychiatric Association).Suche in Google Scholar
APA (2013). Diagnostic and Statistical Manual of Mental Disorders-5 (Washington, DC, USA: American Psychiatric Association).Suche in Google Scholar
Baranek, G.T., David, F.J., Poe, M.D., Stone, W.L., and Watson, L.R. (2006). Sensory experiences questionnaire: Discriminating sensory features in young children with autism, developmental delays, and typical development. J. Child. Psychol. Psychiatry 47, 591–601.10.1111/j.1469-7610.2005.01546.xSuche in Google Scholar PubMed
Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., and Clubley, E. (2001). The autism-spectrum quotient (AQ): evidence from Asperger syndrome/high functioning autism, males and females, scientists and mathematicians. J. Autism Dev. Disord. 31, 5–17.10.1023/A:1005653411471Suche in Google Scholar PubMed
Baum, S.H., Stevenson, R.A., and Wallace, M.T. (2015). Behavioral, perceptual, and neural alterations in sensory and multisensory function in autism spectrum disorder. Prog. Neurobiol. 134, 140–160.10.1016/j.pneurobio.2015.09.007Suche in Google Scholar PubMed PubMed Central
Baxter, A.J., Brugha, T.S., Erskine, H.E., Scheurer, R.W., Vos, T., and Scott, J.G. (2015). The epidemiology and global burden of autism spectrum disorders. Psychol. Med. 45, 601–613.10.1017/S003329171400172XSuche in Google Scholar PubMed
Ben-Sasson, A., Hen, L., Fluss, R., Cremak, S., Engel-Yeger, B., and Gal, E. (2009). A meta-analysis of sensory modulation symptoms in individuals with Autism Spectrum Disorders. J. Autism Dev. Disord. 39, 1–11.10.1007/s10803-008-0593-3Suche in Google Scholar PubMed
Bitsika, V., Sharpley, C., and Mills, R. (2016). How are Sensory Features associated with seven anxiety disorders in boys with Autism Spectrum Disorder? Int. J. Dev. Neurosci. 50, 47–54.10.1016/j.ijdevneu.2016.03.005Suche in Google Scholar PubMed
Bosl, W., Tierney, A., Tager-Flusberg, H., and Nelson, C. (2011). EEG complexity as a biomarker for autism spectrum disorder risk. BMC Med. 9, 18.10.1186/1741-7015-9-18Suche in Google Scholar PubMed PubMed Central
Boutros, N. (2011). Historical Review of Electroencephalography in Psychiatry. Standard Electroencephalography in Clinical Psychiatry: A Practical Handbook, First Edition. N. Boutros, S. Galderisi, O. Pogarell, and S. Riggio, eds. (Chichester, UK: John Wiley & Sons).10.1002/9780470974612.ch1Suche in Google Scholar
Bowyer, S.M. (2016). Coherence a measure of the brain networks: past and present. Neuropsychiatr. Electrophysiol. 2, 1–12.10.1186/s40810-015-0015-7Suche in Google Scholar
Bronzino, J.D. (2000). Principles of Electroencephalography. The Biomedical Engineering Handbook, Second Edition. J.D. Bronzino, ed. (Boca Raton USA: CRC Press LLC).10.1201/9781420049510.ch15Suche in Google Scholar
Brown, C. and Dunn, W. (2006). The Adolesent/Adult Sensory Profile (New York, USA: NCS Pearson).Suche in Google Scholar
Brown, C., Tollefson, N., Dunn, W., Cromwell, R., and Filion, D. (2001). The adult sensory profile: patterns of sensory processing. Am. J. Occup. Ther. 55, 75–82.10.5014/ajot.55.1.75Suche in Google Scholar PubMed
Catarino, A., Andrade, A., Churches, O., Wagner, A.P., Baron-Cohen, S., and Ring, H. (2013). Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence. Mol. Autism 4, 1–14.10.1186/2040-2392-4-1Suche in Google Scholar PubMed PubMed Central
Clarke, A.R., Barry, R.J., Indraratna, A., Dupuy, F.E., McCarthy, R., and Selikowitz, M. (2016). EEG activity in children with Asperger’s syndrome. Clin. Neurophysiol. 127, 442–451.10.1016/j.clinph.2015.05.015Suche in Google Scholar PubMed
Clery, H., Andersson, F., Bonnet-Brilhault, F., Philippe, A., Wicker, B., and Gomot, M. (2013). fMRI investigation of visual change detection in adults with autism. NeuroImage Clin. 2, 303–312.10.1016/j.nicl.2013.01.010Suche in Google Scholar PubMed PubMed Central
Coben, R., Clarke, A.R., Hudspeth, W., and Barry, R. J. (2008). EEG power and coherence in autistic spectrum disorder. Clin. Neurophysiol. 119, 1002–1009.10.1016/j.clinph.2008.01.013Suche in Google Scholar PubMed
Cohen, J. (1992). A power primer. Psychol. Bull. 112, 155–159.10.1037/0033-2909.112.1.155Suche in Google Scholar PubMed
David, O., Cosmelli, D., and Friston, K.J. (2003). Evaluation of different measures of functional connectivity using a neural mass model. NeuroImage 21, 659–673.10.1016/j.neuroimage.2003.10.006Suche in Google Scholar PubMed
Duffy, F.H. and Als, H. (2012). A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls-a large case control study. BMC Med. 10, 1–18.10.1186/1741-7015-10-64Suche in Google Scholar PubMed PubMed Central
Duffy, F.H., Shankardass, A., McAnulty, G.B., and Als, H. (2013). The relationship of asperger’s syndrome to autism: a preliminary EEG coherence study. BMC Med. 11, 1–12.10.1186/1741-7015-11-175Suche in Google Scholar PubMed PubMed Central
Dunn, W. (1999). Sensory Profile (San Antonio, TX, USA: The Psychological Corporation).Suche in Google Scholar
Dunn, W. (2014). Sensory Profile 2: User’s Manual (San Antonio, TX, USA: The Psychological Corporation).Suche in Google Scholar
Elhabashy, H., Raafat, O., Afifi, L., Raafat, H., and Abdullah, K. (2015). Quantitative EEG in autistic children. Egypt. J. Neurol. Psychiatry Neurosurg. 52, 176–182.10.4103/1110-1083.162031Suche in Google Scholar
Elsabbagh, M., Divan, G., Koh, Y.J., Kim, Y.S., Kauchali, S., Marcin, C., Montiel-Nava, C., Patel, V., Paula, C.S., Wang, C., et al. (2012). Global prevalence of autism and other pervasive developmental disorders. Autism Res. 5, 160–179.10.1002/aur.239Suche in Google Scholar PubMed PubMed Central
Frye, R.E. (2015). Prevalence, significance and clinical characteristics of seizures, epilepsy and subclinical electrical activity in autism. N. Am. J. Med. Sci. 3, 113–122.Suche in Google Scholar
Gould, J. and Ashton-Smith, J. (2011). Missed diagnosis or misdiagnosis? Girls and women on the autism spectrum. GAP 12, 34–41.Suche in Google Scholar
Hochhauser, M. and Engel-Yeger, B. (2010). Sensory processing abilities and their relation to participation in leisure activities among children with high-functioning autism spectrum disorder (HFASD). Res. Autism Spectr. Disord. 4, 746–754.10.1016/j.rasd.2010.01.015Suche in Google Scholar
Isler, J.R., Martien, K.M., Grieve, P.G., Stark, R.I., and Herbert, M.R. (2010). Reduced functional connectivity in visual evoked potentials in children with autism spectrum disorder. Clin. Neurophysiol. 121, 2035–2043.10.1016/j.clinph.2010.05.004Suche in Google Scholar PubMed
Jeste, S.S. and Nelson, C.A. (2009). Event related potentials in the understanding of autism spectrum disorders: an analytical review. J. Autism Dev. Disord. 39, 495–510.10.1007/s10803-008-0652-9Suche in Google Scholar PubMed
Jochaut, D., Lehongre, K., Saltovitch, A., Devauchelle, A.D., Olasagasti, I., Chabane, N., and Giraud, A.L. (2015). Aypical coordination of cortical oscillations in response to speech in autism. Front. Hum. Neurosci. 171, 1–12.10.3389/fnhum.2015.00171Suche in Google Scholar
Kern, J., Trivedi, M., Garver, C., Grannemann, B., Andrews, A., and Salva, J. (2006). The pattern of sensory processing abnormalities in autism. Autism 10, 480–494.10.1177/1362361306066564Suche in Google Scholar PubMed
Lai, M.C., Lombardo, M.V., and Baron-Cohen, S. (2014). Autism. Lancet 383, 896–910.10.1016/S0140-6736(13)61539-1Suche in Google Scholar PubMed
Landa, L., Krpoun, Z., Kolarova, M., and Kasparek, T. (2014). Event-related potentials and their applications. Act. Nerv. Super. 56, 17–23.10.1007/BF03379603Suche in Google Scholar
Lane, A., Molloy, C., and Bishop, S. (2014). Classification of children with Autism Spectrum Disorder by sensory subtype: a case for sensory-based phenotypes. Autism Res. 7, 322–333.10.1002/aur.1368Suche in Google Scholar PubMed
Lazarev, V.V., Pontes, A., Mitrofanov, A.A., and deAzevedo, L.C. (2010). Interhemispheric asymmetry in EEG photic driving coherence in childhood autism. Clin. Neurophysiol. 121, 145–152.10.1016/j.clinph.2009.10.010Suche in Google Scholar PubMed
Lazarev, V.V., Pontes, A., Mitrofanov, A.A., and deAzevedo, L.C. (2015). Reduced interhemispheric connectivity in childhood autism detected by electroencephalographic photic driving coherence. J. Autism Dev. Disord. 45, 537–547.10.1007/s10803-013-1959-8Suche in Google Scholar PubMed
Linden, M. and Gunkelman, J. (2013). QEEG-Guided Neurofeedback for Autism: Clinical Observations and Outcomes. Imaging the Brain in Autism. M.L. Casanova, A.S. El-Baz and J.S. Suri, eds. (New York, NY. USA: Springer), pp. 45–60.10.1007/978-1-4614-6843-1_3Suche in Google Scholar
Lord, C., Rutter, M., and Le 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, 659–685.10.1007/BF02172145Suche in Google Scholar PubMed
Lord, C., Risi, S., Lambrecht, L., Cook, E.H., Leventhal, B.L., DiLavore, P.C., Pickles, A., and 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, 205–223.10.1023/A:1005592401947Suche in Google Scholar PubMed
Ludlow, A., Mohr, B., Whitmore, A., Garagnani, M., Pulvermuller, F., and Gutierrez, R. (2014). Auditory processing and sensory behaviours in children with autism spectrum disorders as revealed by mismatch negativity. Brain Cogn. 86, 55–63.10.1016/j.bandc.2014.01.016Suche in Google Scholar PubMed
Lyall, K., Croen, L., Daniels, J., Fallin, M.D., Ladd-Acosta, C., Lee, B.K., Lee, B.K., Park, B.Y., Snyder, N.W., Schendel, D., et al. (2017). The changing epidemiology of autism spectrum disorders. Ann. Rev. Public Health 38, 81–102.10.1146/annurev-publhealth-031816-044318Suche in Google Scholar PubMed PubMed Central
Machado, C., Estévez, M., Leisman, G., Melillo, R., Rodríguez, R., DeFina, P., Hernández, A., Pérez-Nellar, J., Naranjo, R., Chinchilla, M., et al. (2015). QEEG spectral and coherence assessment of autistic children in three different experimental conditions. J. Autism Dev. Disord. 45, 406–424.10.1007/s10803-013-1909-5Suche in Google Scholar PubMed PubMed Central
Marco, E.J., Hinkley, L.B., Hill, S.S., and Nagarajan, S.S. (2011). Sensory processing in autism: a review of neurophysiologic findings. Pediatr. Res. 69, 48R–54R.10.1203/PDR.0b013e3182130c54Suche in Google Scholar PubMed PubMed Central
Mathewson, K.J., Jetha, M.K., Drmic, I.E., Bryson, S.E., Goldberg, J.O., and Schmidt, L.A. (2012). Regional EEG alpha power, coherence, and behavioral symptomatology in autism spectrum disorder. Clin. Neurophysiol. 123, 1798–1809.10.1016/j.clinph.2012.02.061Suche in Google Scholar PubMed
Matlis, S., Boric, K., Chu, C.J., and Kramer, M.A. (2015). Robust disruptions in electroencephalogram cortical oscillations and large-scale functional networks in autism. BMC Neurol. 15, 1–17.10.1186/s12883-015-0355-8Suche in Google Scholar PubMed PubMed Central
Maxwell, C.R., Villalobos, M.E., Schultz, T.R., Herpertz-Dahlmann, B., Konrad, K., and Kohls, G. (2015). Atypical laterality of resting gamma oscillations in autism spectrum disorders. J. Autism Dev. Disord. 45, 292–297.10.1007/s10803-013-1842-7Suche in Google Scholar PubMed PubMed Central
Milne, E. (2011). Increased intra-participant variability in children with autistic spectrum disorders: evidence from single-trial analysis of evoked EEG. Front. Psychol. 2, 1–12.10.3389/fpsyg.2011.00051Suche in Google Scholar PubMed PubMed Central
Mohammad-Rezazadeh, I., Frohlich, J., Loo, S.K., and Jeste, S.S. (2016). Brain connectivity in autism spectrum disorder. Curr. Opin. Neurol. 29, 137–147.10.1097/WCO.0000000000000301Suche in Google Scholar PubMed PubMed Central
Murias, M., Webb, S.J., Greenson, J., and Dawson, G. (2007). Resting state cortical connectivity reflected in EEG coherence in individuals with autism. Biol. Psychiatry 62, 270–273.10.1016/j.biopsych.2006.11.012Suche in Google Scholar PubMed PubMed Central
Nowicka, A., Cygan, H.B., Tacikowski, P., Ostaszewski, P., and Kus, R. (2016). Name recognition in autism: EEG evidence of altered patterns of brain activity and connectivity. Mol. Autism 7, 1–14.10.1186/s13229-016-0102-zSuche in Google Scholar PubMed PubMed Central
O’Donnell, S., Deitz, J., Kartin, D., Nalty, T., and Dawson, G. (2012). Sensory processing, problem behavior, adaptive behavior, and cognition in preschool children with Autism Spectrum Disorders. Am. J. Occup. Ther. 66, 586–594.10.5014/ajot.2012.004168Suche in Google Scholar PubMed
O’Reilly, C., Lewis, J.E., and Elsabbagh, M. (2017). Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies. PLoS One 12, e0175870.10.1371/journal.pone.0175870Suche in Google Scholar PubMed PubMed Central
Olejarczyk, E., Marzetti, L., Pizzella, V., and Zappasodi, F. (2017). Comparison of connectivity analyses for resting state EEG data. J. Neural Eng. 14, 1–13.10.1088/1741-2552/aa6401Suche in Google Scholar PubMed
Orekhova, E.V., Elsabbagh, M., Jones, E.J., Dawson, G., Charman, T., Johnson, M.H., and Team, B. (2014). EEG hyper-connectivity in high-risk infants is associated with later autism. J. Neurodev. Disord. 6, 1866–1955.10.1186/1866-1955-6-40Suche in Google Scholar PubMed PubMed Central
Pistorius, T., Aldrich, C., Auret, L., and Pineda, J. (2013). Early Detection of risk of autism spectrum disorder based on recurrence quantification analysis of electroencephalographic signals. Paper presented at the Neural Engineering (NER) 6th International IEEE/EMBS Conference.10.1109/NER.2013.6695906Suche in Google Scholar
Reynolds, S., Lane, S., and Gennings, C. (2010). The moderating role of sensory overresponsivity in HPA activity. J. Atten. Disord. 13, 468–478.10.1177/1087054708329906Suche in Google Scholar PubMed
Reynolds, S., Lane, S., and Thacker, L. (2011). Sensory processing, physiological stress, and sleep behaviors in children with and without autism spectrum disorders. OTJR 32, 246–257.10.3928/15394492-20110513-02Suche in Google Scholar
Schauder, K.B. and Bennetto, L. (2016). Toward an interdisciplinary understanding of sensory dysfunction in autism spectrum disorder: an integration of the neural and symptom literatures. Front. Neurosci. 10, 1–18.10.3389/fnins.2016.00268Suche in Google Scholar
Schomer, D.L. and Lopes da Silva, F.H. (2011). Niedermeyer’s Electroencephalography (Philadelphia, USA: Lippincott Williams and Wilkins).Suche in Google Scholar
Schwartz, S., Kessler, R., Gaughan, T., and Buckley, A.W. (2017). Electroencephalogram coherence patterns in autism: an updated review. Pediatr. Neurol. 67, 7–22.10.1016/j.pediatrneurol.2016.10.018Suche in Google Scholar PubMed
Seth, A.K., Barrett, A.B., and Barnett, L. (2015). Granger causality analysis in neuroscience and neuroimaging. J. Neurosci. 35, 3293–3297.10.1523/JNEUROSCI.4399-14.2015Suche in Google Scholar PubMed
Sharpley, C., Bitsika, V., and Mills, R. (2016). Are Sensory Processing Features associated with depression in boys with an ASD? J. Autism Dev. Disord. 46, 242–252.10.1007/s10803-015-2569-4Suche in Google Scholar
Simon, D.M., Damiano, C.R., Woynaroski, T., Ibanez, L.V., Murias, M., Stone, W.L., Wallace, M.T., and Cascio, C.J. (2017). Neural correlates of sensory hyporesponsiveness in toddlers at high risk for autism spectrum disorder. J. Autism Dev. Disord. 47, 2710–2722.10.1007/s10803-017-3191-4Suche in Google Scholar PubMed
Sporns, O. (2014). Towards network substrates of brain disorders. Brain 137, 2117–2118.10.1093/brain/awu148Suche in Google Scholar PubMed
Srinivasan, R. and Nunez, P.L. (2012). Electroencephalography. Encyclopedia of Human Behavior. V.S. Ramchandran, ed. (Burlington, MA, USA: Academic Press), pp. 15–23.10.1016/B978-0-12-375000-6.00395-5Suche in Google Scholar
Stam, C.J. and van Dijk, B.W. (2002). Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets. Physica D 163, 236–251.10.1016/S0167-2789(01)00386-4Suche in Google Scholar
Stevenson, R.A., Siemann, J.K., Schneider, B.C., Eberly, H.E., Woynaroski, T.G., Camarata, S.M., and Wallace, M.T. (2014). Multisensory temporal integration in autism spectrum disorders. J. Neurosci. 343, 691–697.10.1523/JNEUROSCI.3615-13.2014Suche in Google Scholar PubMed PubMed Central
Thatcher, R.W., Biver, C.J., and North, D.M. (2004). EEG and brain connectivity: a tutorial.Suche in Google Scholar
Tseng, M., Fu, C., Cermak, S., Lu, L., and Shieh, J. (2011). Emotional and behavioral problems in preschool children with autism: relationship with sensory processing dysfunction. Res. Autism Spectr. Disord. 5, 1441–1450.10.1016/j.rasd.2011.02.004Suche in Google Scholar
van Wijngaarden-Cremers, P., van Eeten, E., Broen, W., van Deurzen, P., Oosterling, I., and Van der Gaag, R. (2014). Gender and age differences in the core triad of impairments in Autism Spectrum Disorders: a systematic review and meta-analysis. J. Autism Dev. Disord. 44, 627–635.10.1007/s10803-013-1913-9Suche in Google Scholar PubMed
Wang, J., Barstein, J., Ethridge, L.E., Mosconi, M.W., Takarae, Y., and Sweeney, J.A. (2013). Resting state EEG abnormalities in autism spectrum disorders. J. Neurodev. Disord. 5, 1–14.10.1186/1866-1955-5-24Suche in Google Scholar PubMed PubMed Central
Webb, S.J., Bernier, R., Henderson, H.A., Johnson, M.H., Jones, E.J.H., Lerner, M.D., McPartland, J.C., Nelson, C.A., Rojas, D.C., Townsend, J., et al. (2015). Guidelines and best practices for electrophysiological data collection, analysis and reporting in autism. J. Autism Dev. Disord. 45, 425–443.10.1007/s10803-013-1916-6Suche in Google Scholar PubMed PubMed Central
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Artikel in diesem Heft
- Frontmatter
- Alpha-synuclein in salivary gland as biomarker for Parkinson’s disease
- Determining the early corticospinal-motoneuronal responses to strength training: a systematic review and meta-analysis
- The role of neurovascular unit damage in the occurrence and development of Alzheimer’s disease
- Functions of adiponectin signaling in regulating neural plasticity and its application as the therapeutic target to neurological and psychiatric diseases
- A review of the use of EEG connectivity to measure the neurological characteristics of the sensory features in young people with autism
- Multiple sclerosis – the remarkable story of a baffling disease
- Melatonin and its anti-glioma functions: a comprehensive review
- The role of fibroblast growth factors and their receptors in gliomas: the mutations involved
- Application of quercetin in neurological disorders: from nutrition to nanomedicine