Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-14T19:18:17.582Z Has data issue: false hasContentIssue false
  • English
  • Français

Effects of multisensory integration processes on response inhibition in adolescent autism spectrum disorder

Published online by Cambridge University Press:  18 July 2016

W. X. Chmielewski ,
N. Wolff ,
M. Mückschel ,
V. Roessner  and
C. Beste
W. X. Chmielewski
Affiliation:
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Germany
N. Wolff
Affiliation:
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Germany
M. Mückschel
Affiliation:
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Germany
V. Roessner
Affiliation:
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Germany
C. Beste*
Affiliation:
Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Germany Experimental Neurobiology, National Institute of Mental Health, Klecany, Czech Republic
*
*Address for correspondence: Dr C. Beste, Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Schubertstrasse 42, D-01309 Dresden, Germany. (Email: christian.beste@uniklinikum-dresden.de)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

In everyday life it is often required to integrate multisensory input to successfully conduct response inhibition (RI) and thus major executive control processes. Both RI and multisensory processes have been suggested to be altered in autism spectrum disorder (ASD). It is, however, unclear which neurophysiological processes relate to changes in RI in ASD and in how far these processes are affected by possible multisensory integration deficits in ASD.

Method

Combining high-density EEG recordings with source localization analyses, we examined a group of adolescent ASD patients (n = 20) and healthy controls (n = 20) using a novel RI task.

Results

Compared to controls, RI processes are generally compromised in adolescent ASD. This aggravation of RI processes is modulated by the content of multisensory information. The neurophysiological data suggest that deficits in ASD emerge in attentional selection and resource allocation processes related to occipito-parietal and middle frontal regions. Most importantly, conflict monitoring subprocesses during RI were specifically modulated by content of multisensory information in the superior frontal gyrus.

Conclusions

RI processes are overstrained in adolescent ASD, especially when conflicting multisensory information has to be integrated to perform RI. It seems that the content of multisensory input is important to consider in ASD and its effects on cognitive control processes.

Keywords

Autism spectrum disorderEEGexecutive functionsmultisensory processingresponse inhibition
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 13 , October 2016 , pp. 2705 - 2716
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

APA (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th edn. American Psychiatric Publishing: Arlington, VA.Google Scholar
Aschenbach, TM (1991). Integrative Guide for the 1991CBCL/4-18, YSR, and TRF Profiles. Department of Psychiatry: University of Vermont.Google Scholar
Bari, A, Robbins, TW (2013). Inhibition and impulsivity: behavioral and neural basis of response control. Progress in Neurobiology 108, 44–79.Google Scholar
Baum, SH, Stevenson, RA, Wallace, MT (2015). Behavioral, perceptual, and neural alterations in sensory and multisensory function in autism spectrum disorder. Progress in Neurobiology, 140–160.Google Scholar
Bertone, A, Mottron, L, Jelenic, P, Faubert, J (2005). Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity. Brain 128, 2430–2441.Google Scholar
Beste, C, Dziobek, I, Hielscher, H, Willemssen, R, Falkenstein, M (2009). Effects of stimulus-response compatibility on inhibitory processes in Parkinson's disease. European Journal of Neuroscience 29, 855–860.Google Scholar
Beste, C, Ness, V, Falkenstein, M, Saft, C (2011). On the role of fronto-striatal neural synchronization processes for response inhibition–evidence from ERP phase-synchronization analyses in pre-manifest Huntington's disease gene mutation carriers. Neuropsychologia 49, 3484–3493.Google Scholar
Beste, C, Saft, C (2015). Action selection in a possible model of striatal medium spiny neuron dysfunction: behavioral and EEG data in a patient with benign hereditary chorea. Brain Structure and Function 220, 221–228.Google Scholar
Beste, C, Willemssen, R, Saft, C, Falkenstein, M (2010). Response inhibition subprocesses and dopaminergic pathways: basal ganglia disease effects. Neuropsychologia 48, 366–373.CrossRefGoogle ScholarPubMed
Bishop, DVM, Norbury, CF (2005). Executive functions in children with communication impairments, in relation to autistic symptomatology 2: response inhibition. Autism 9, 29–43.Google Scholar
Bokura, H, Yamaguchi, S, Kobayashi, S (2001). Electrophysiological correlates for response inhibition in a Go/NoGo task. Clinical Neurophysiology 112, 2224–2232.CrossRefGoogle Scholar
Bruin, KJ, Wijers, AA, van Staveren, AS (2001). Response priming in a go/nogo task: do we have to explain the go/nogo N2 effect in terms of response activation instead of inhibition? Clinical Neurophysiology 112, 1660–1671.Google Scholar
Campbell, J, Sharma, A (2013). Compensatory changes in cortical resource allocation in adults with hearing loss. Frontiers in Systems Neuroscience 7, 71.Google Scholar
Chmielewski, WX, Beste, C (2015). Action control processes in autism spectrum disorder – insights from a neurobiological and neuroanatomical perspective. Progress in Neurobiology 124, 49–83.Google Scholar
Chmielewski, WX, Mückschel, M, Dippel, G, Beste, C (2015 a). Concurrent information affects response inhibition processes via the modulation of theta oscillations in cognitive control networks. Brain Structure and Function. doi:10.1007/s00429-015-1137-1.Google Scholar
Chmielewski, WX, Mückschel, M, Roessner, V, Beste, C (2014). Expectancy effects during response selection modulate attentional selection and inhibitory control networks. Behavioural Brain Research 274C, 53–61.Google Scholar
Chmielewski, WX, Mückschel, M, Stock, A-K, Beste, C (2015 b). The impact of mental workload on inhibitory control subprocesses. NeuroImage 112, 96–104.CrossRefGoogle ScholarPubMed
Chmielewski, WX, Roessner, V, Beste, C (2015 c). Predictability and context determine differences in conflict monitoring between adolescence and adulthood. Behavioural Brain Research 292, 10–18.Google Scholar
Cohen, MX (2014). Analyzing Neural Time Series Data. Theory and Practice. MIT Press.Google Scholar
Dilling, H, Mombour, W, Schmidt, MH, Schulte-Markwort, E, Remschmidt, H (eds) (2015). Internationale Klassifikation psychischer Störungen ICD-10 Kapitel V (F). Klinisch-diagnostische Leitlinien. Huber: Bern.Google Scholar
Dippel, G, Beste, C (2015). A causal role of the right inferior frontal cortex in implementing strategies for multi-component behaviour. Nature Communications 6, 6587.Google Scholar
Duerden, EG, Taylor, MJ, Soorya, LV, Wang, T, Fan, J, Anagnostou, E (2013). Neural correlates of inhibition of socially relevant stimuli in adults with autism spectrum disorder. Brain Research 1533, 80–90.CrossRefGoogle ScholarPubMed
Falkenstein, M, Hoormann, J, Hohnsbein, J (1999). ERP components in Go/Nogo tasks and their relation to inhibition. Acta Psychologica 101, 267–291.CrossRefGoogle ScholarPubMed
Foxe, JJ, Molholm, S, Del Bene, VA, Frey, H-P, Russo, NN, Blanco, D, Saint-Amour, D, Ross, LA (2015). Severe multisensory speech integration deficits in high-functioning school-aged children with Autism Spectrum Disorder (ASD) and their resolution during early adolescence. Cerebral Cortex (New York) 25, 298–312.Google ScholarPubMed
Friedman, D, Cycowicz, YM, Gaeta, H (2001). The novelty P3: an event-related brain potential (ERP) sign of the brain's evaluation of novelty. Neuroscience and Biobehavioral Reviews 25, 355–373.Google Scholar
Fuchs, M, Kastner, J, Wagner, M, Hawes, S, Ebersole, JS (2002). A standardized boundary element method volume conductor model. Clinical Neurophysiology 113, 702–712.CrossRefGoogle ScholarPubMed
Geisler, MW, Murphy, C (2000). Event-related brain potentials to attended and ignored olfactory and trigeminal stimuli. International Journal of Psychophysiology 37, 309–315.Google Scholar
Geurts, HM, Verté, S, Oosterlaan, J, Roeyers, H, Sergeant, JA (2004). How specific are executive functioning deficits in attention deficit hyperactivity disorder and autism? Journal of Child Psychology and Psychiatry 45, 836–854.Google Scholar
Gotham, K, Pickles, A, Lord, C (2009). Standardizing ADOS scores for a measure of severity in autism spectrum disorders. Journal of Autism and Developmental Disorders 39, 693–705.Google Scholar
Gotham, K, Risi, S, Pickles, A, Lord, C (2007). The autism diagnostic observation schedule: revised algorithms for improved diagnostic validity. Journal of Autism and Developmental Disorders 37, 613–627.Google Scholar
Herrmann, CS, Knight, RT (2001). Mechanisms of human attention: event-related potentials and oscillations. Neuroscience and Biobehavioral Reviews 25, 465–476.Google Scholar
Hughes, C (1996). Control of action and thought: normal development and dysfunction in autism: a research note. Journal of Child Psychology and Psychiatry 37, 229–236.CrossRefGoogle ScholarPubMed
Huster, RJ, Enriquez-Geppert, S, Lavallee, CF, Falkenstein, M, Herrmann, CS (2013). Electroencephalography of response inhibition tasks: functional networks and cognitive contributions. International Journal of Psychophysiology 87, 217–233.Google Scholar
Jodo, E, Kayama, Y (1992). Relation of a negative ERP component to response inhibition in a Go/No-go task. Electroencephalography and Clinical Neurophysiology 82, 477–482.Google Scholar
Kana, RK, Keller, TA, Minshew, NJ, Just, MA (2007). Inhibitory control in high-functioning autism: decreased activation and underconnectivity in inhibition networks. Biological Psychiatry 62, 198–206.Google Scholar
Kok, A (1986). Effects of degradation of visual stimuli on components of the event-related potential (ERP) in go/nogo reaction tasks. Biological Psychology 23, 21–38.Google Scholar
Kwakye, LD, Foss-Feig, JH, Cascio, CJ, Stone, WL, Wallace, MT (2011). Altered auditory and multisensory temporal processing in autism spectrum disorders. Frontiers in Integrative Neuroscience 4, 129.Google Scholar
Lee, PS, Yerys, BE, Rosa, AD, Foss-Feig, J, Barnes, KA, James, JD, VanMeter, J, Vaidya, CJ, Gaillard, WD, Kenworthy, LE (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, 1787–1794.Google Scholar
Lord, C, Risi, S (1998). Frameworks and methods in diagnosing autism spectrum disorders. Mental Retardation and Developmental Disabilities Research Reviews 4, 90–96.3.0.CO;2-0>CrossRefGoogle Scholar
Lord, C, Rutter, M, Couteur, AL (1994). Autism diagnostic interview-revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. Journal of Autism and Developmental Disorders 24, 659–685.Google Scholar
Makeig, S, Bell, AJ, Jung, T-P, Sejnowski, TJ (1996). Independent component analysis of electroencephalographic data. In Advances in Neural Information Processing Systemss, Vol. 8 (ed. Touretzky, D.S.), pp. 141–151. MIT Press: Cambridge, Massachsetts, USA.Google Scholar
Mazziotta, J, Toga, A, Evans, A, Fox, P, Lancaster, J, Zilles, K, Woods, R, Paus, T, Simpson, G, Pike, B, Holmes, C, Collins, L, Thompson, P, MacDonald, D, Iacoboni, M, Schormann, T, Amunts, K, Palomero-Gallagher, N, Geyer, S, Parsons, L, Narr, K, Kabani, N, Le Goualher, G, Boomsma, D, Cannon, T, Kawashima, R, Mazoyer, B (2001). A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philosophical Transactions of the Royal Society of London. Series B 356, 1293–1322.Google Scholar
Menon, V, Adleman, NE, White, CD, Glover, GH, Reiss, AL (2001). Error-related brain activation during a Go/NoGo response inhibition task. Human Brain Mapping 12, 131–143.Google Scholar
Minshew, NJ, Hobson, JA (2008). Sensory sensitivities and performance on sensory perceptual tasks in high-functioning individuals with autism. Journal of Autism and Developmental Disorders 38, 1485–1498.CrossRefGoogle ScholarPubMed
Mückschel, M, Smitka, M, Hermann, A, von der Hagen, M, Beste, C (2015). Deep brain stimulation in the globus pallidus compensates response inhibition deficits: evidence from pantothenate kinase-associated neurodegeneration. Brain Structure and Function 221, 2251–2257.Google Scholar
Mückschel, M, Stock, A-K, Beste, C (2014). Psychophysiological mechanisms of interindividual differences in goal activation modes during action cascading. Cerebral Cortex 24, 2120–2129.Google Scholar
Nieuwenhuis, S, Yeung, N, Cohen, JD (2004). Stimulus modality, perceptual overlap, and the go/no-go N2. Psychophysiology 41, 157–160.Google Scholar
Nieuwenhuis, S, Yeung, N, van den Wildenberg, W, Ridderinkhof, KR (2003). Electrophysiological correlates of anterior cingulate function in a go/no-go task: effects of response conflict and trial type frequency. Cognitive, Affective, and Behavioral Neuroscience 3, 17–26.Google Scholar
Nunez, PL, Pilgreen, KL (1991). The spline-Laplacian in clinical neurophysiology: a method to improve EEG spatial resolution. Journal of Clinical Neurophysiology 8, 397–413.Google Scholar
Ozonoff, S, Strayer, DL, McMahon, WM, Filloux, F (1994). Executive function abilities in autism and tourette syndrome: an information processing approach. Journal of Child Psychology and Psychiatry 35, 1015–1032.Google Scholar
Pascual-Marqui, RD (2002). Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods and Findings in Experimental and Clinical Pharmacology 24(Suppl. D), 5–12.Google Scholar
Peelle, JE, Troiani, V, Wingfield, A, Grossman, M (2010). Neural processing during older adults’ comprehension of spoken sentences: age differences in resource allocation and connectivity. Cerebral Cortex (New York, N.Y.: 1991) 20, 773–782.Google Scholar
Petermann, F, Petermann, U (2011). Wechsler Intelligence Scale for Children, 4th edn. Pearson Assessment: Frankfurt/Main.Google Scholar
Pfefferbaum, A, Ford, JM, Weller, BJ, Kopell, BS (1985). ERPs to response production and inhibition. Electroencephalography and Clinical Neurophysiology 60, 423–434.Google Scholar
Quetscher, C, Yildiz, A, Dharmadhikari, S, Glaubitz, B, Schmidt-Wilcke, T, Dydak, U, Beste, C (2015). Striatal GABA-MRS predicts response inhibition performance and its cortical electrophysiological correlates. Brain Structure and Function 220, 3555–3564.Google Scholar
Raymaekers, R, van der Meere, J, Roeyers, H (2004). Event-rate manipulation and its effect on arousal modulation and response inhibition in adults with high functioning autism. Journal of Clinical and Experimental Neuropsychology 26, 74–82.Google Scholar
Roche, RAP, Garavan, H, Foxe, JJ, O'Mara, SM (2004). Individual differences discriminate event-related potentials but not performance during response inhibition. Experimental Brain Research 160, 60–70.Google Scholar
Salazar, RF, Kayser, C, König, P (2004). Effects of training on neuronal activity and interactions in primary and higher visual cortices in the alert cat. Journal of Neuroscience 24, 1627–1636.Google Scholar
Schintu, S, Hadj-Bouziane, F, Dal Monte, O, Knutson, KM, Pardini, M, Wassermann, EM, Grafman, J, Krueger, F (2014). Object and space perception – is it a matter of hemisphere? Cortex 57, 244–253.Google Scholar
Schmajuk, M, Liotti, M, Busse, L, Woldorff, MG (2006). Electrophysiological activity underlying inhibitory control processes in normal adults. Neuropsychologia 44, 384–395.Google Scholar
Schmitz, N, Rubia, K, Daly, E, Smith, A, Williams, S, Murphy, DGM (2006). Neural correlates of executive function in autistic spectrum disorders. Biological Psychiatry 59, 7–16.Google Scholar
Sekihara, K, Sahani, M, Nagarajan, SS (2005). Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction. NeuroImage 25, 1056–1067.Google Scholar
Sheehan, DV, Sheehan, KH, Shytle, RD, Janavs, J, Bannon, Y, Rogers, JE, Milo, KM, Stock, SL, Wilkinson, B (2010). Reliability and validity of the mini international neuropsychiatric interview for children and adolescents (MINI-KID). Journal of Clinical Psychiatry 71, 313–326.Google Scholar
Shumway, S, Farmer, C, Thurm, A, Joseph, L, Black, D, Golden, C (2012). The ADOS calibrated severity score: relationship to phenotypic variables and stability over time. Autism Research 5, 267–276.CrossRefGoogle ScholarPubMed
Simson, R, Vaughan, HG Jr., Ritter, W (1977). The scalp topography of potentials in auditory and visual discrimination tasks. Electroencephalography and Clinical Neurophysiology 42, 528–535.Google Scholar
Stevenson, RA, Siemann, JK, Woynaroski, TG, Schneider, BC, Eberly, HE, Camarata, SM, Wallace, MT (2014). Evidence for diminished multisensory integration in autism spectrum disorders. Journal of Autism and Developmental Disorders 44, 3161–3167.Google Scholar
Sugimoto, F, Katayama, J (2013). Somatosensory P2 reflects resource allocation in a game task: assessment with an irrelevant probe technique using electrical probe stimuli to shoulders. International Journal of Psychophysiology 87, 200–204.Google Scholar
Wessel, JR, Aron, AR (2015). It's not too late: the onset of the frontocentral P3 indexes successful response inhibition in the stop-signal paradigm. Psychophysiology 52, 472–480.Google Scholar
Supplementary material: File

Chmielewski supplementary material

Figures S1-S2

Download Chmielewski supplementary material(File)
File 2 MB