Elsevier

Neuroscience & Biobehavioral Reviews

Volume 68, September 2016, Pages 848-861
Neuroscience & Biobehavioral Reviews

Dysfunction of sensory oscillations in Autism Spectrum Disorder

https://doi.org/10.1016/j.neubiorev.2016.07.016Get rights and content

Highlights

  • Altered sensory and perceptual function is recognized as an important characteristic of Autism Spectrum Disorder (ASD).

  • Disrupted oscillatory synchronization in ASD is observable in numerous sensory and perceptual tasks and in multiple frequency bands of the oscillatory hierarchy.

  • Oscillatory changes in ASD are consistent with a disturbance in the balance of excitation and inhibition, as well as disruption of thalamic function.

  • Altered network synchronization makes contributions to both perceptual enhancement and impairment in ASD.

Abstract

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD.

Introduction

Autism Spectrum Disorder (ASD) is a developmental disability characterized by persistent deficits in social communication and interaction, restricted interests, and repetitive behaviors (American Psychiatric Association, 2013). An estimated 1 in 68 children born in the United States will receive a diagnosis of ASD, and the disorder carries enormous social and economic costs (Buescher et al., 2014, Developmental Disabilities Monitoring Network Surveillance Year Principal et al., 2014, Karst and Van Hecke, 2012). This high prevalence and socioeconomic cost have motivated numerous investigations to better understand the brain bases of ASD. Studies utilizing functional magnetic resonance imaging (fMRI) have consistently indicated that patterns of structural (Shukla et al., 2010) and functional (Dinstein et al., 2011) connectivity are significantly altered in individuals with ASD. Postmortem anatomical inquiries have likewise indicated that the microstructure of cortical circuitry is fundamentally altered in ASD (Casanova et al., 2006, McKavanagh et al., 2015). Investigations examining connectivity on more rapid time scales utilizing electroencephalography (EEG) (Coben et al., 2014) and magnetoencephalography (MEG) (Ye et al., 2014) have similarly indicated that connectivity alterations are a characteristic feature of ASD. These connectivity alterations have been proposed as both a leading biomarker and the origin of the behavioral dysfunction characteristic of the disorder (Geschwind and Levitt, 2007). Network-based analyses have revealed that the nature of connectivity differences among individuals with ASD is highly individualized (Hahamy et al., 2015). However, how these changes in network structure impact neural processing and emerge as the collection of phenotypes that characterize ASD is poorly understood, and consequently has become an area of important investigation. Studies using EEG and MEG have uncovered differences in rhythmically modulated networks known as oscillators. This oscillatory dysfunction in ASD may form the bridge between dysfunction at the cellular and local levels, changes in large-scale network organization, and the sensory and perceptual processing differences that represent a core feature of the disorder.

Section snippets

Sensory and perceptual function in ASD

Alterations in sensory and perceptual processes have long been recognized to be present in ASD (Marco et al., 2011). Recent revisions to diagnostic criteria have now acknowledged that these sensory and perceptual dysfunctions constitute a core feature of ASD (American Psychiatric Association, 2013). Intriguingly, investigations focused on sensory function in ASD have revealed that, even within a single sensory modality such as vision, both strengths and weaknesses can be present. For example,

Oscillatory contributions to sensory encoding

The rhythmic nature of neural activity has been recognized since the earliest attempts at non-invasive measurement (Berger, 1929). These rhythmic fluctuations are referred to as oscillations, and have been characterized over a large range of frequencies (here denoted as delta: δ, 1–4 Hz, theta: θ, 4–8 Hz, alpha: α, 8–14 Hz, beta: β, 15–30 Hz, and gamma: γ, >30 Hz, although the exact ranges vary in the literature). The role of these oscillations in neural computation is of great interest and has

Gamma abnormalities in ASD and their role in sensory and perceptual processing

Gamma (γ, >30 Hz) band responses have been proposed to play a key role in the encoding of sensory evidence in local networks and are strongly modulated in response to sensory stimulation. Importantly, the physiological origins of γ oscillations in sensory cortices are well known; high γ (>80 Hz) oscillations largely correspond with spiking activity while low γ (<80 Hz) oscillations primarily correspond with localized network synchronization (Ray and Maunsell, 2011). Activity in the 30–45 Hz range

Alpha abnormalities in ASD and their role in sensory and perceptual processing

Alpha (α, 8–14 Hz) is one of the most distinct frequency ranges in human neural activity, notable for its significant deviation from the expected relationship between frequency and power. For most oscillatory neural activity, total power is inversely related to frequency, but human alpha power is notably higher than would be expected from this relationship (Buzsaki and Draguhn, 2004). This atypical power distribution implies additional functional significance for this frequency band, which has

Oscillatory organization is disrupted in ASD

The presence of consistent deficits in ASD in both the α and γ frequency ranges suggests that these may be coupled in meaningful ways and that these changes may result in reduced flexibility of moderate and high frequency synchronization. Such a mechanism is offered by oscillatory hierarchies, in which low frequency δ and θ oscillations play an instrumental role in shaping higher frequency oscillations. One of the best studied of these hierarchical relationships is the entrainment of θ

Methodological challenges and opportunities

The finding of increased power over a wide range of frequencies highlights an important methodological challenge for oscillatory research in ASD. If intrinsic broadband power is chronically elevated then procedures which determine power changes compared to baseline systematically underestimate both evoked and induced power. This effect may account for some of the notable discrepancies between task based and resting state investigations of oscillatory function in ASD. A striking example of this

Mechanistic account of altered oscillator function in ASD

The consistent finding of impaired power modulation and reduced phase synchronization across multiple frequency bands suggests that disruption of oscillatory processes is a strong contributor to the neurobiological differences that underpin ASD. In attempting to link these more network-based changes to cellular and microcircuit substrates, disruption of the balance between excitation and inhibition has received substantial attention (Rubenstein and Merzenich, 2003). High frequency oscillations

Oscillatory function and neurobiologically inspired theories of autism

Theoretical perspectives on ASD have long recognized that the basis of neurologic impairment may lie in disruption of processes related to information transfer and information integration. The Weak Central Coherence (WCC) model, for example, posits that processing differences in ASD result from deficits of information integration across distributed and distant cortical circuits while localized processing remains intact (Happe and Frith, 2006). From a biological perspective, such processes would

Diagnostic and treatment implications of oscillator dysfunction

Perturbations in sensory and perceptual function are being increasingly recognized as core features of ASD that contribute to lifelong disability (American Psychiatric Association, 2013). The recognition of brain oscillations and synchronization as playing an important role in pathology raises two critical questions. First, whether oscillations can be utilized for evaluation of treatment regimes, and second, whether oscillatory function itself is a potential avenue of treatment. There is

Conclusions and future directions

Disruptions in oscillatory synchronization are ubiquitous during sensory and perceptual processing in ASD. While synchronization alterations in ASD are not limited to these processes, deficits in these areas are particularly important given the renewed emphasis on sensory dysfunction as a core impairment that potentially emerges early in development (and that may then underpin the develop of more complex and higher-order functions). These disruptions have been found in multiple sensory

Acknowledgements

This work was supported by NIH U54 HD083211, NIH DC010927, CA183492, HD83211, and by the Wallace Foundation and the Simons Foundation Autism Research Initiative. The funding sources played no role in the writing or submission of this article. The authors declare no competing interests.

References (175)

  • I. Dinstein et al.

    Disrupted neural synchronization in toddlers with autism

    Neuron

    (2011)
  • I. Dinstein et al.

    Unreliable evoked responses in autism

    Neuron

    (2012)
  • A.K. Engel et al.

    Temporal binding and the neural correlates of sensory awareness

    Trends Cogn. Sci.

    (2001)
  • B. Engelhard et al.

    Inducing gamma oscillations and precise spike synchrony by operant conditioning via brain-machine interface

    Neuron

    (2013)
  • A. Ewald et al.

    Estimating true brain connectivity from EEG/MEG data invariant to linear and static transformations in sensor space

    Neuroimage

    (2012)
  • P. Fries et al.

    The gamma cycle

    Trends Neurosci.

    (2007)
  • W. Gaetz et al.

    GABA estimation in the brains of children on the autism spectrum: measurement precision and regional cortical variation

    Neuroimage

    (2014)
  • M.J. Gandal et al.

    Validating gamma oscillations and delayed auditory responses as translational biomarkers of autism

    Biol. Psychiatry

    (2010)
  • D.H. Geschwind et al.

    Autism spectrum disorders: developmental disconnection syndromes

    Curr. Opin. Neurobiol.

    (2007)
  • S. Hanslmayr et al.

    Prestimulus oscillations predict visual perception performance between and within subjects

    Neuroimage

    (2007)
  • S. Heim et al.

    Early gamma oscillations during rapid auditory processing in children with a language-learning impairment: changes in neural mass activity after training

    Neuropsychologia

    (2013)
  • R.F. Helfrich et al.

    Entrainment of brain oscillations by transcranial alternating current stimulation

    Curr. Biol.: CB

    (2014)
  • B. Hutcheon et al.

    Resonance, oscillation and the intrinsic frequency preferences of neurons

    Trends Neurosci.

    (2000)
  • J.R. Isler et al.

    Reduced functional connectivity in visual evoked potentials in children with autism spectrum disorder

    Clin. Neurophysiol.

    (2010)
  • B.H. Jansen et al.

    The effect of the phase of prestimulus alpha activity on the averaged visual evoked response

    Electroencephalogr. Clin. Neurophysiol.

    (1991)
  • A.W. Keizer et al.

    The effect of gamma enhancing neurofeedback on the control of feature bindings and intelligence measures

    Int. J. Psychophysiol.

    (2010)
  • C.L. Keown et al.

    Local functional overconnectivity in posterior brain regions is associated with symptom severity in autism spectrum disorders

    Cell Rep.

    (2013)
  • W. Klimesch et al.

    EEG alpha oscillations: the inhibition-timing hypothesis

    Brain Res. Rev.

    (2007)
  • V.V. Lazarev et al.

    EEG photic driving: right-hemisphere reactivity deficit in childhood autism. A pilot study

    Int. J. Psychophysiol.

    (2009)
  • V.V. Lazarev et al.

    Interhemispheric asymmetry in EEG photic driving coherence in childhood autism

    Clin. Neurophysiol.

    (2010)
  • B.H. Lee et al.

    Autism spectrum disorder and epilepsy: disorders with a shared biology

    Epilepsy Behav.

    (2015)
  • Z. Liu et al.

    Finding thalamic BOLD correlates to posterior alpha EEG

    Neuroimage

    (2012)
  • L. Ai et al.

    The phase of prestimulus alpha oscillations affects tactile perception

    J. Neurophysiol.

    (2014)
  • T. Akam et al.

    Oscillatory multiplexing of population codes for selective communication in the mammalian brain

    Nat. Rev. Neurosci.

    (2014)
  • American Psychiatric Association

    Diagnostic and Statistical Manual of Mental Disorders

    (2013)
  • A. Antal et al.

    Transcranial alternating current stimulation (tACS)

    Front. Hum. Neurosci.

    (2013)
  • P. Barttfeld et al.

    Organization of brain networks governed by long-range connections index autistic traits in the general population

    J. Neurodev. Disord.

    (2013)
  • M. Bazhenov et al.

    Self-sustained rhythmic activity in the thalamic reticular nucleus mediated by depolarizing GABAA receptor potentials

    Nat. Neurosci.

    (1999)
  • H. Berger

    Uber das electrenenkephalogramm des menschen [On the electroencephalogram of humans]

    Arch. Pscyhiatrica Nervkrankh

    (1929)
  • J.I. Berman et al.

    Alpha-to-gamma phase-amplitude coupling methods and application to autism spectrum disorder

    Brain Connect.

    (2015)
  • A. Bertone et al.

    Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity

    Brain

    (2005)
  • A. Bonnel et al.

    Enhanced pitch sensitivity in individuals with autism: a signal detection analysis

    J. Cogn. Neurosci.

    (2003)
  • B. Boroojerdi et al.

    Reduction of human visual cortex excitability using 1-Hz transcranial magnetic stimulation

    Neurology

    (2000)
  • W. Bosl et al.

    EEG complexity as a biomarker for autism spectrum disorder risk

    BMC Med.

    (2011)
  • L. Bouvet et al.

    Auditory stream segregation in autism spectrum disorder: benefits and downsides of superior perceptual processes

    J. Autism Dev. Disord.

    (2016)
  • M.S. Brown et al.

    Increased glutamate concentration in the auditory cortex of persons with autism and first-degree relatives: a (1)H-MRS study

    Autism Res.

    (2013)
  • I. Buard et al.

    Altered oscillation patterns and connectivity during picture naming in autism

    Front. Hum. Neurosci.

    (2013)
  • A.V. Buescher et al.

    Costs of autism spectrum disorders in the United Kingdom and the United States

    JAMA Pediatr.

    (2014)
  • E.T. Bullmore et al.

    Complex brain networks: graph theoretical analysis of structural and functional systems

    Nat. Rev. Neurosci.

    (2009)
  • E. Bullmore et al.

    The economy of brain network organization

    Nat. Rev. Neurosci.

    (2012)
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