Multisensory Integration in Autism Spectrum Disorders: Investigating

Transcription

Running head: MULTISENSORY INTEGRATION IN ASD
Multisensory Integration in Autism Spectrum Disorders: Investigating the
Susceptibility to Auditory-Guided Visual Illusions
Vanessa Bao
Department of Educational and Counselling Psychology
McGill University, Montreal
August, 2013
A thesis submitted to McGill University in partial fulfillment of the requirements
of the degree of Masters of Arts in School/Applied Child Psychology
Vanessa Bao, 2013
MULTISENSORY INTEGRATION IN ASD
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Acknowledgements
I would like to begin by expressing how immensely grateful I am for the
continued support of my supervisor, Dr. Armando Bertone. I am so appreciative
of the time and effort you dedicated to responding to my thousands of emails and
editing and re-editing my work over the past two years. More than anything I
appreciate the constant guidance you have given me, the patience you had in
response to my unending questions and the knowledge you have imparted that has
been crucial in shaping me as a student, researcher and as a person.
I also want to thank Victoria Doobay. I could not have asked for a better
lab partner, and testing buddy. Thank you for helping me navigate all the
obstacles that came with testing and coursework, and for making the whole
process seem a little less daunting and making it feel a lot more positive!
To all the members of the PNLab, I appreciate all the help you gave me
throughout the process of piloting, testing and presenting. I especially want to
thank Jackie Guy for being patient in answering innumerable questions and for
being a great sounding board for me. Thank you to Domenic Tullo. You were
incredibly dedicated and your help with testing was very much appreciated.
I am indebted to the participants recruited from the CETED database at
Rivière-des-Prairies Hospital and their families. Their time and enthusiasm made
this study possible.
To my family, thank you for enduring my complaints. Mom and Dad, your
unconditional love and support made such a tremendous difference. Thank you
for always being there to listen and for doing everything you possibly could to
make this whole process easier for me. To my husband, Nick Caruso, thank you
for your unwavering support and love. You have given me the strength to get
through the deadlines, the long hours, and the recurring fear that I would never
complete this thesis. I could not have accomplished what I have in the past few
years without your love, encouragement, and ridiculous positivity.
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Table of Contents
Acknowledgements ............................................................................................... 2
List of Tables ......................................................................................................... 6
List of Figures ........................................................................................................ 7
Abstract .................................................................................................................. 8
Résumé ................................................................................................................... 9
Overview and Objectives .................................................................................... 10
Literature Review ............................................................................................... 11
Autism Spectrum Disorder ............................................................................... 11
Sensory Abnormalities and Sensory Processing ............................................... 12
Cognitive Theories of ASD .............................................................................. 13
Multisensory Integration ................................................................................... 15
Multisensory Integration in ASD ...................................................................... 18
Multisensory integration of socio-communicative
sensory information .......................................................................................18
Multisensory integration of lower-level (non-social)
sensory information .......................................................................................22
Rationale for the Current Study .................................................................... 26
Hypotheses ....................................................................................................... 27
Methods ................................................................................................................ 28
Participants .........................................................................................................28
ASD group ......................................................................................................27
Typically-developing comparison group .......................................................28
Testing location and procedure for participants ...........................................29
Apparatus .......................................................................................................... 31
Stimuli and Procedure ....................................................................................... 31
Results .................................................................................................................. 34
Analysis of Accuracy ........................................................................................ 35
Analysis of RT .................................................................................................. 38
Analysis of Age Effects on Accuracy and RT .................................................. 41
Discussion............................................................................................................. 43
Multisensory Facilitation .................................................................................. 44
Susceptibility to the Fusion and Fission Illusions ............................................. 45
Age Effects ........................................................................................................ 48
Clinical Implications ......................................................................................... 49
Limitations & Future Directions ....................................................................... 50
Conclusion & Summary ..................................................................................... 52
References ............................................................................................................ 54
Appendix A .......................................................................................................... 64
Telephone Script for Participant Recruitment ... Error! Bookmark not defined.
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Appendix B .......................................................................................................... 65
Consent Form – Adult Participants ................................................................... 65
Appendix C .......................................................................................................... 68
Consent Form – Child & Adolescent Participants ............................................ 68
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List of Tables
Table 1. Means, Standard Deviations, Ranges and Mean Comparisons of
Participant Variables by Group ..............................................................................35
Table 2. Mean Accuracy Scores and Standard Errors for Each Trial Type Across
Groups ....................................................................................................................36
Table 3. Mean Accuracy Scores and Standard Errors for Each Trial Type Based
on Group ................................................................................................................38
Table 4. Mean Reaction Times and Standard Errors for Each Trial Type Across
Groups ....................................................................................................................39
Table 5. Mean Reaction Times and Standard Errors of Each Trial Type by Group
................................................................................................................................41
Table 6. Correlation between chronological age and performance (Accuracy and
RT) for fission and fusion trials for both ASD and TD groups .............................42
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List of Figures
Figure 1. Illustration of stimulus presentation for the flash-beep illusion task .....32
Figure 2. Bar graph representing the difference in accuracy scores on each trial
type between the ASD and Control groups ............................................................37
Figure 3. Bar graph representing the difference in reaction times on each trial
type between the ASD and Control groups ............................................................40
Figure 4. Scatterplot representing the significant correlation between age and RT
on the 2F1B fusion trial for the TD control group .................................................43
Abstract
Autism Spectrum Disorders (ASD) are characterized by impairments in
social and communicative functioning as well as repetitive behaviours and
interests. Sensory processing abnormalities have also been found to be prevalent
in ASD, with atypical Multisensory Integration (MSI) hypothesized to underlie
the core features of ASD. The goal of the current study was to investigate MSI
abilities in ASD by testing susceptibility to auditory-guided visual illusions to
determine whether impaired MSI is present when using lower-level stimuli that
are not socio-communicative in nature. Adolescents and adults with ASD (n=20)
and TD individuals (n=20) were shown to have similar susceptibility to a fission
illusion where two beeps (i.e., auditory stimulus) cause the illusory perception of
two flashes (i.e., visual stimulus) when only one flash was presented. However,
the ASD group was significantly more susceptible to the fusion illusion, where
one beep presented with two flashes causes the illusory perception that only one
flash was presented. Results indicate that MSI may be intact in ASD for lowerlevel sensory information void of socio-communicative content (i.e., faces and
speech sounds). Results have implications for sensory integration therapy and for
the understanding of the core features of ASD.
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Résumé
Les troubles du spectre autistiques (TSA) sont caractérisés par une
déficience au niveau du fonctionnement social et communicatif ainsi que par des
comportements et intérêts répétitifs. De plus, des anomalies au niveau du
traitement de l’information sensorielle sont communes chez les individus autistes.
Plusieurs chercheurs ont proposé que l’intégration multisensorielle (IMS) pourrait
sous-tendre les caractéristiques fondamentales des TSA. L’objectif de la présente
étude est d’étudier la capacité des individus autistes à intégrer des stimuli simples
(c.-à-d., non-sociaux) en examinant la sensibilité aux illusions visuelles
provoquées par l’information auditive. Les adolescent et adultes autistes (n=20) et
développant typiquement (n=20) démontrent un niveau de sensibilité semblable à
l’illusion fission (c.-à-d., la perception illusoire de deux stimuli visuels lors de la
présentation simultanée de deux stimuli auditifs et d’un stimulus visuel). Le
groupe autiste était significativement plus sensible à l’illusion fusion (c.-à-d., la
perception illusoire d’un seul stimulus visuel lors de la présentation simultanée
d’un stimulus auditifs et de deux stimuli visuels). Les résultats indiquent que
l’IMS chez les autistes est probablement intacte au niveau inférieur. Les
conclusions tirées par différentes études investiguant l’IMS, que l’IMS est altérée
chez les autistes, pourraient être attribuables à l’utilisation de stimuli sociocommunicatifs (c. visages, langage). Les résultats ont des implications pour la
thérapie d’intégration sensorielle et pour la compréhension des caractéristiques
fondamentales du TSA.
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Overview and Objectives
Although not traditionally part of the diagnostic criteria, sensory
processing atypicalities in Autism Spectrum Disorders (ASD) have been of
particular interest in the field of ASD research due to the prevalence of sensory
issues in this population and the notion that these atypicalities may underlie the
core features of ASD (i.e., social and communicative impairments, repetitive and
restricted interests and behaviours). The ability to integrate information from
multiple sensory modalities at once, Multisensory Integration (MSI), is of
particular interest because of its implications for effective and adaptive interaction
with the environment. Research has begun to indicate that individuals with ASD
may have an impaired or altered ability to integrate sensory information. However,
the vast majority of these studies have used stimuli that are socio-communicative
in nature making it difficult to parse apart impaired MSI from impaired
perception/processing of social and communicative information.
The goal of the present study is to determine whether an impairment in
MSI exists in ASD in response to stimuli that is simple and non-social. In other
words, the aim is to identify whether individuals with ASD exhibit atypical
integration at the lower level of sensory processing. In the present study,
susceptibility to auditory-guided visual illusions is assessed in order to identify
MSI processes in individuals with ASD.
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Literature Review
Autism Spectrum Disorder
Autism Spectrum Disorder (ASD), a developmental disorder of genetic
origin whose aetiology is as of yet still unclear (Abrahams & Geschwind 2008),
With prevalence rates that are thought to number from .3 to .6% of the population
(Fombonne, 2003; Lord, Cook, Leventhal & Amaral, 2000), ASD is one of the
most prevalent clinical conditions across the lifespan. Behaviourally, ASD is
currently characterized by social and communication impairments (e.g., lack of
shared enjoyment and reciprocity, non-verbal communication deficits, stereotyped
speech, delayed language acquisition) as well as the presence of restricted or
repetitive patterns of behaviour and interests (American Psychiatric Association,
2013).
Although diagnostically, ASD is defined by the core features of social and
communicative deficits and repetitive behaviours, additional features are
frequently observed in individuals with ASD (Frith & Happé, 1994; Simmons et
al., 2009). In addition to the core symptoms, sensory processing has been
identified as atypical in ASD as early as the first descriptions of the disorder made
by Leo Kanner (Kanner, 1943). Caminha and Lampreia (2012) highlighted studies
that found that between 70 and 80% of individuals with ASD had sensory
abnormalities. A study by Leekam, Nieto, Libby, Wing and Gould (2007) found
that according to parental report, more than 90% of the children studied exhibited
sensory abnormalities. For example, individuals with ASD often exhibit an
aversion to certain sensory stimuli (e.g., withdrawing from noises like a baby
crying or the sound of a lawnmower, avoiding certain textures or smells) or
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alternatively, seek out sensory experiences through stimulatory behaviours (e.g.,
peering, echoing, tapping surfaces, twirling items in front of their eyes; Kern et al.,
2006; Lovaas, Newsom & Hickman, 1987).
Sensory Abnormalities and Sensory Processing
In addition to exhibiting sensory defensiveness as well as sensory-seeking
behaviours, individuals with ASD also process incoming sensory stimuli
differently. Sensory processing abnormalities have been cited in numerous
experimental studies as well as firsthand accounts from individuals with ASD
(O’Neill & Jones, 2007). Kern et al. (2006) found that individuals with ASD
processed auditory, visual, tactile and oral sensory information significantly
differently than typically developing (TD) control subjects. Marco, Hinkley, Hill
and Nagarajan (2011) reviewed neuropsychological findings on sensory
processing in autism and determined that research has supported the view that
there exists altered auditory processing as early as the level of the primary
auditory cortex as well as abnormal processing of visual information at the lower
level. Moreover, a meta-analysis revealed that sensory processing abnormalities
appear to be present in ASD regardless of age or severity of symptoms (BenSasson, Hen, Fluss, Cermak, Engel-Yeger & Gal, 2009).
These sensory processing differences have been thought to possibly
underlie some of the core characteristics of ASD (Caminha & Lampreia, 2012;
Frith & Happé, 1994; Marco, Hinkley, Hill & Nagarajan, 2011). In other words,
sensory processing deficits may contribute in part to the social and
communicative impairments and the restricted/repetitive behaviours and interests
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seen in individuals with ASD. For instance, Behrmann, Thomas & Humphreys
(2006) proposed that the extensively researched deficit in face processing and
recognition may not be an entirely social deficit, but that lower level visual
processing deficits may be contributing to this difficulty. Similarly, in their EEG
study, Maekawa et al. (2011) found that individuals with high-functioning ASD
had abnormal lower-level (non-social) visual processing. They suggested that
these atypical visual processes might be underlying the face processing
difficulties as well as other social difficulties that are common to ASD. Hilton,
Graver and LaVesser (2007) found a positive relationship between the degree of
sensory processing deficits and social competence, which indicates that sensory
processing issues may be contributing to the severity of social impairment.
Another study has even shown that the sensory processing abnormalities in ASD
appear to be related to adaptive behaviour skills (Lane, Young, Baker & Angley,
2010). According to the study, more severe sensory processing difficulties were
associated with a higher prevalence of maladaptive behaviours.
Cognitive Theories of ASD
Various cognitive theories have been put forth to explain the perceptual
and sensory processing differences that exist in ASD and to attempt to make the
link between sensory processing and the core features of ASD. The Weak Central
Coherence (WCC) theory was proposed in response to the prevailing Theory of
Mind perspective (Baron-Cohen, Leslie & Frith, 1985), which did not adequately
explain the disorder as a whole and only accounted for some of its characteristics
(Frith & Happé, 1994; Happé & Frith 2006). Central coherence is purported to be
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the typical approach to information processing whereby individuals tend to
process information to obtain general meaning or a global representation of
information (Frith & Happé, 1994; Happé, 1994; Rajendran & Micthell, 2007).
The WCC account goes beyond simply exploring the core features of autism by
attempting to explain the non-core features of ASD (e.g., sensory abnormalities)
and by taking into account not only the areas of impairment in autism but also the
areas of strength that have repeatedly been shown to exist (Happé, 1994). The
WCC theory hypothesizes that individuals with ASD do not integrate information
typically and instead appear to focus on parts rather than the whole of
representations (Frith & Happé, 1994; Frith, 1997). This account would not only
explain the perceptual processing abnormalities that have been found in ASD but
also speak to the difference in integrating sensory information from the same
sensory modality or from various modalities at once.
The temporal binding deficit hypothesis has also been advanced to explain
the neural underpinnings of the core and non-core features of ASD (Brock, Brown,
Boucher & Rippon, 2002). The authors expanded on the WCC theory by
providing a hypothesis for the neural mechanisms that lead to the features of ASD.
According to Brock, Brown, Boucher and Rippon (2002): “ whereas typical brain
development involves the emergence of functionally specialized but nevertheless
integrated regions, brain development in autism involves the emergence of
functionally specialized brain regions that become increasingly isolated from each
other over time.” Temporal binding is hypothesized to allow individuals to
integrate incoming information and make sense of new information (Brock et al.,
2002). The authors explain that temporal binding is impaired between local
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networks in the brains of individuals with ASD, which would lead to the “weak
coherence” of information in ASD. In sum, this theory accepts the WCC theory at
the observable level but proposes that impaired integration of neural networks
underlies the core features of ASD as well as atypical perceptual processes
necessitating integrative analysis.
Yet another theory developed to explain perceptual and sensory
differences in ASD is the Enhanced Perceptual Functioning (EFP) model of
autism (Mottron & Burack, 2001; Mottron, Dawson, Soulières, Hubert & Burack,
2006). The EFP theory was originally proposed as an alternative way of
understanding perceptual functioning and cognitive processes in ASD. The EFP
theory hypothesizes that the pattern of behaviour as well as the specific neural and
cognitive processes in ASD are caused by more independent and enhanced
functioning of perceptual processes in individuals with ASD as compared to TD
individuals (Mottron et al., 2006). According to the theory, perception in ASD is
characterised by a local perceptual bias and enhanced functioning and implication
of low-level perceptual mechanism during both sensory and cognitive tasks in
autism.
Multisensory Integration
One common thread to these cognitive theories is the potential atypical
manner with which sensory information is integrated in ASD, particularly across
modalities (i.e., audition and vision). This is of particular relevance in ASD
research given the sensory-related behaviours that defined its phenotype. There
rarely exist situations in which we are not confronted with sensory information
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from more than one modality (i.e., sight, sound, touch, smell) at once (De Gelder
& Bertelson, 2003). For instance, as we take a walk outside, our brains are
making sense of the various pieces of sensory information: the sight of a bird in a
tree and the sound of its chirping; seeing a fly landing on our arm coupled with
the sensation of it touching us and the sound of its buzzing; listening to a friend
talk over the din of a lawnmower and watching their lips move to make sense of
the information. We must therefore constantly be integrating these pieces of
information to make a unified whole in order to create an accurate representation
of the external environment, interpret it correctly and efficiently, and behave
adaptively in response to it.
Although our senses function largely independently, the brain integrates
the information from these disparate sensory inputs so that the experiences we
have make sense; the brain is organized not only to allow us to distinguish
information from different modalities but also to integrate this information (Stein
& Meredith, 1990). Multisensory integration (MSI) is the process by which
information from multiple sensory modalities are integrated into a whole (Stein &
Meredith, 1993). MSI is what allows us to understand that the sound of chirping
and the sight of a bird are one event and not distinct and unrelated occurrences
and the processes behind integrating sensory information processes is automatic
and largely unconscious (Foxe & Molholm, 2009).
MSI is an automatic process, but the integration of sensory information is
dependent on specific factors (Spence, 2007). For MSI to occur, the sensory
information from each modality needs to be spatially and temporally congruent
(i.e., close enough in space and time to be considered as a single event or
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representation; Hillock et al., 2011; Spence, 2007; Stevenson & Wallace, 2013).
As the temporal or spatial difference between sensory information from multiple
modalities increases, the ability to integrate the two decreases (Hillock, et al.,
2011). Furthermore, cognitive factors, such as whether two pieces of information
are semantically congruent or make sense together, play a role in whether or not
information becomes integrated (Spence, 2007). Not only are there factors at play
to determine whether different pieces of sensory information will be integrated,
there are also specific factors that have been shown to determine how certain
modalities alter the perception of others. Shams, Kamitani & Shimojo (2004) cite
the modality appropriateness hypothesis whereby the modality that is most
relevant for a task will guide the perception of the other modality. Vision has
“higher spatial resolution” so it will dominate and alter the perception of sound on
spatial tasks, but sound, which has a “higher temporal resolution”, will alter the
perception of other sensory modalities on tasks that are more temporal in nature
(Shams, Kamitani & Shimojo, 2004).
The most important advantage of MSI is that these processes allow
individuals to process incoming information more effectively and adaptively
(Foxe & Molholm, 2009; Hillock, Powers, & Wallace, 2011; Stein & Meredith,
1993). In fact, the facilitation conferred by MSI goes beyond what would be
expected due to the mere effect of redundancy (Calvert & Thesen, 2004; Girard,
Pelland, Lepore & Collignon, 2013; Stein, Wallace & Stanford, 1999). What this
means is that, although common sense explains why having twice the sensory
information (i.e., multi-modal information presented together) would lead to
faster responding, the effectiveness and speed of responding to multi-modal
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information is greater than the sum of its parts (i.e., MSI responding is quicker
than what would be expected from summing the response to both unisensory
pieces of information; Iarocci & McDonald, 2006; Stein et al., 1999).
Research in MSI has seen a huge expansion in recent years and its role in
information processing as well as the level at which it operates are starting to
become better understood. A great deal of research has been produced to attempt
to determine the way MSI processes operate at the neural level and at which level
of processing MSI takes place (Calvert & Thesen, 2004; Stein & Meredith, 1993;
Shams, et al., 2004). It was previously assumed that MSI occurred at the later
stages of processing (i.e., the association cortex), however, recent findings are
beginning to suggest that this process can also occur at the lower-levels of
processing within unimodal primary visual and auditory neural areas (Calvert &
Thesen, 2004). Brain areas that were thought to only be unisensory areas have
been implicated in MSI (Calvert & Thesen, 2004; Shams et al., 2004). These
findings have implications not only for the way in which MSI is studied in the TD
population but also for how MSI processes are conceptualized in ASD.
Multisensory Integration in ASD
As previously described, various cognitive theories have hypothesized that
there may exist an impairment in ASD with regard to integrating information
(Brock et al., 2002; Frith & Happé, 1994; Mottron & Burack, 2001). In fact, it has
been suggested that the root of many of the core features of ASD may be related
to this inability or atypicality in integrating information from multiple sensory
modalities at once (Iarocci & McDonald, 2006; Marco et al., 2011). Foxe and
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Molholm (2009) provide an explanation for the potential link between impaired
MSI and the core features of ASD. The authors state that if an individual were
unable to properly integrate sensory information, “the environment would be a
much more complex and confusing space” (Foxe & Molholm, 2009). These
authors suggest that individuals with ASD would be constantly inundated with too
much incoherent information. By being unable to make sense of the massive
amounts of sensory information they are constantly being bombarded with,
individuals with ASD withdraw and attempt to reduce the confusion. In addition,
the authors explain that if MSI is impaired, other parts of the brain may be
recruited to help process the overwhelming amount of sensory stimulation,
resulting in decreased resources available for other functions (i.e., executive
functions). Foxe and Molholm (2009) hypothesize that this may also be a reason
for the “lack of cognitive flexibility” that is often seen in ASD.
Researchers have attempted to identify the neural mechanisms at work
behind the integration of sensory information in ASD. Findings have suggested
that structural abnormalities in the cerebellum may be causing difficulty with
shifting attention between auditory and visual sensory information (Iarocci &
McDonald, 2006). Brandwein et al. (2013) used a simple reaction time paradigm
to study MSI abnormalities in ASD at the behavioural and neural level. They
found that individuals with ASD showed diminished MSI facilitation at the
behavioural level (i.e., responses on a reaction time task) as well as less effective
and less widespread neural integration.
Multisensory integration of socio-communicative sensory information.
While research on MSI abilities in ASD have expanded, there remain many
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questions to be answered with regard to the sensory integration profile of
individuals with ASD. Much of the information on MSI in ASD has originated
from studies examining the integration of sensory stimuli that are sociocommunicative in nature (i.e., speech and faces; Brandwein et al., 2013; Mongillo
et al., 2008). The McGurk effect provides a great example of MSI and has been
the paradigm of choice for studying MSI in TD individuals as well as in ASD
(Foxe & Molholm, 2009; Iarocci & McDonald, 2006). In the McGurk illusion
task, individuals are presented with an auditory stimulus (e.g., a voice saying the
syllable “ba”) and a visual stimulus that does not match (e.g., a person seen
mouthing the syllable “ga”; McGurk & MacDonald, 1976). The illusion leads
people to integrate what they are hearing and seeing into the perception of hearing
the syllable “da”; the visual stimulus affects the perception of the auditory
information (Iarocci & McDonald, 2006; McGurk & MacDonald, 1976).
This illusion has been found to be extremely robust in TD individuals and
has been employed in multiple studies to assess MSI in ASD. Williams, Massaro,
Peel, Bosseler and Suddendorf (2004) found that individuals with ASD showed a
diminished McGurk effect as compared to TD individuals. Woynaroski et al.
(2013) showed that there was an expanded temporal binding window in the ASD
group in a McGurk task where the time between the presentation of each stimulus
was varied. They even found a relationship between multisensory speech
perception and the severity of symptoms in ASD. A study by Taylor, Isaac, and
Milne (2010) suggested that the reduced MSI in ASD seen with the McGurk
effect might be more of a delay in development rather than a deficit. In light of the
fact that the McGurk illusion is such a strong example of MSI, it might be
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tempting to draw the conclusion that MSI is impaired in ASD. However, it is
possible that difficulty with the McGurk task or other MSI tasks using sociocommunicative stimuli is due to the social aspects of these tasks rather than an
inherent difficulty integrating sensory information (Mongillo et al., 2008; Wlliams,
Massaro, Peel, Bosseler, & Suddendorf, 2004).
Smith and Bennetto (2007) tested ASD participants on a task that required
them to understand speech in noisy conditions. In such a paradigm, TD
individuals benefit from the addition of visual information (i.e., seeing the face of
the person who is speaking) because it allows them to better decode what is being
said in noisy conditions (Smith & Bennetto, 2007). Individuals with ASD
demonstrated less of a benefit than TD individuals when given visual information
to help understand speech in noisy conditions. In other words, they showed less
MSI facilitation than the TD group did. This method not only examines MSI of
audiovisual information, it also implicates lip-reading as an automatic process that
we use to help us decode speech in everyday life. Due to the fact that we know
individuals with ASD have face processing deficits and diminished lip-reading
abilities, the results may be more indicative of these deficits rather than impaired
MSI at the lower level (Donohue, Darling & Mitroff, 2012; Silverman, Bennetto,
Campana, & Tanenhaus, 2010).
Another study of MSI using socio-communicative stimuli showed that
individuals with ASD were slower than TD individuals to process speech when
gestures accompanied the speech (Silverman, et al., 2010). These results indicate
not only that there was no MSI facilitation in ASD, in fact, the addition of
information from another sensory modality hindered information processing. The
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authors suggested that the findings indicate impaired MSI of “higher order
information” (i.e., more complex information such as speech and gestures).
However the results cannot speak to an impairment in MSI at the lower level of
processing (i.e., basic information, the first steps of perception). Bebko, Weiss,
Demark, and Gomez (2006) found that young children with ASD had impaired
MSI when processing linguistic stimuli, but also noted that a deficit in integrating
and processing information from multiple modalities may be specific to language.
Yet another study found that while individuals with ASD did not differ from a TD
group at the behavioural level on a task of audiovisual speech integration, EEG
results indicated the presence of a higher order processing difficulty (i.e., complex
phonological integration processes were impaired in ASD; Magnée, de Gelder,
van Engeland, & Kemner, 2008). Charbonneau et al. (2013) sought to evaluate the
integration of audiovisual multisensory integration of emotional sensory
information (i.e., visual and auditory representations of fear and disgust) in
individuals with ASD. Their results were twofold: individuals with ASD did not
benefit from the presentation of information from multiple modalities (i.e., they
had reduced multisensory facilitation) as much as TD individuals did, and
furthermore the ASD group was less efficient at discriminating emotional
information. Their results indicate that individuals with ASD may have altered or
impaired processing and integration of sensory information that conveys
emotional meaning.
Taken together, these findings indicate that there exists some difficulty
integrating socially- or emotionally-laden information such as speech, faces and
gestures in ASD. However, identifying and integrating faces, speech and gestures
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are considered to be higher-level processes (Donohue, Darling, & Mitroff, 2012).
In order to better understand MSI processes in ASD, we must look at lower-level
integration of more basic information. The use of socio-communicative stimuli in
MSI research confounds results: are the impairments in MSI evidenced by these
studies due to inherent difficulties with integrating information or due to the core
social and communicative deficits that are at the core of ASD?
Multisensory integration of lower-level (non-social) sensory
information. Few studies have explicitly investigated MSI abilities in ASD using
lower-level, non-social stimuli, and the ones that have, have shown mixed results.
One recent study by our group (Collignon et al., 2013) assessed multisensory
facilitation in ASD using a non-social, cognitive paradigm. The “pip and pop”
visual search paradigm was used, whereby during a visual search, the colour of a
target changes and a synchronous sound (i.e., the pip) is presented. Typically
developing individuals exhibit multisensory facilitation when the sound is paired
with the target’s colour change (i.e., the target is identified more easily; Collignon
et al., 2013). Results indicated that although individuals with ASD outperformed
control participants on some visual search conditions, they do not benefit from the
facilitatory pip; the pip and pop effect was absent in ASD group. The authors
suggest that the absence of this effect might be indicative of abnormal lower-level
sensory integration. Mongillo et al. (2008), on the other hand, tested participants
on audiovisual integration tasks involving human faces and speech as well as
tasks involving non-social stimuli (i.e., visual presentation of bouncing balls with
matched or mismatched bouncing sounds) and found that whereas the
performance of ASD participants on social tasks differed significantly from the
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performance of TD individuals, there was no difference on the tasks using nonsocial stimuli. These findings, which stand in contrast to those found in the
Collignon et al. (2013) study, suggest that MSI impairments may be more socially
based in ASD.
Visual illusions have also been studied in the context of sensory
integration research in ASD. In a study by Happé (1996), the susceptibility of
individuals with ASD to visual illusions (e.g., Titchener circles, Muller-Lyer
figures, Ponzo illusion) was compared to TD control participants. Happé found
that individuals with ASD were less susceptible to visual illusions and
hypothesized that this occurred because individuals with ASD failed to integrate
information at the lower-level because visual illusions require integration of
information. Ropar and Mitchell (1999) sought to replicate Happé’s findings
because of the implication that, since susceptibility to visual illusions is such a
basic part of perception, if individuals with ASD were not susceptible their
perception would be drastically different than that of TD individuals (Mitchell &
Ropar, 2004; Ropar & Mitchell, 1999). It appeared that susceptibility to visual
illusions did not differ between ASD and TD groups. They further tested
susceptibility to visual illusions in a subsequent study and once again found that
there was no difference between groups and that performance on visuospatial
tasks did not predict susceptibility to illusions (Ropar & Mitchell, 2001). These
results appear to indicate that individuals with ASD are not impaired at the basic
level of perception and sensory integration when using non-social stimuli.
An interesting study by Kwakye, Foss-Feig, Cascio, Stone and Wallace
(2011) used simple lower level stimuli in temporal order judgement tasks to
25
determine whether the temporal factors of MSI are altered in ASD. As previously
mentioned, information needs to be temporally congruent in order to be
integrated; longer gaps between stimulus presentations make it difficult to
integrate sensory information (Hillock, et al., 2011). Kwakye et al. (2011) found
that the multisensory binding window is larger is ASD. In other words, they
perceive stimuli as integrated even when the temporal gap is expanded. The
authors interpreted the results as indicating that MSI is intact for lower-level
stimuli in ASD and suggested that this altered temporal processing might underlie
some of the core features of ASD. This study expanded previous work by FossFeig et al. (2010), which also found that there existed an expanded window of
temporal integration for simple, non-social stimuli. Foss-Feig et al. (2010) used
the flash-beep illusion paradigm to test the hypothesized expanded temporal
integration window in ASD and found that individuals with ASD had an
expanded temporal binding window when tested with the flash-beep task.
First identified by Shams, Kamitani and Shimojo (2000), the flash-beep
illusion is of particular importance for the current study. By presenting varying
numbers of flashes and beeps at the same time, Shams et al. (2000) discovered
that when a single flash is presented with multiple beeps, the flash is actually
perceived to be multiple flashes (i.e., fission illusion). This flash-beep illusion is
robust in TD individuals and is a manifestation of the automaticity with which
multisensory information is processed and integrated (Foxe & Molholm, 2009;
Shams, Kamitani, & Shimojo, 2000; Shams, Kamitani, & Shimojo, 2002).
Andersen, Tiipana and Sams (2004) extended the results with the finding of a
fusion illusion (i.e., one beep presented with multiple flashes causes the
26
perception of one flash) and further support for the presence of the fission illusion
(i.e., multiple beeps presented with one flash cause the perception of multiple
flashes). Keane, Rosenthal, Chun and Shams (2010) used methods similar to those
developed by Shams et al. (2000) to test temporal numerosity and MSI in ASD.
They found no difference between the performance of participants with ASD and
TD participants (Keane, Rosenthal, Chun, & Shams, 2010). In another study, it
was found that the flash-beep illusion effect was present in high functioning
adults with ASD (van der Smagt, van Engeland & Kemner, 2007). Taken together,
these results are pointing toward intact lower level multisensory integration and
indicate that general assumptions of MSI from self-report, behavioural measures,
and neurological measures might be more accurately attributable to the sociocommunicative deficits that are the hallmark of ASD.
Rationale for the Current Study
The present study will bolster and expand upon the extant knowledge
available about lower-level MSI in ASD. A vast amount of research has been
undertaken to identify integration deficits in ASD, but the majority of these
studies have examined the question using socio-communicative stimuli that may
have confounded results. In contrast there is a relative paucity of information
about the nature of lower level multisensory integration in ASD. Although some
findings have been brought to light with regard to multisensory integration at the
lower level, more work is needed in order to better understand this process so that
we may ultimately be able to guide therapeutic approaches. Sensory integration
therapies are on the rise, but very little is known about the nature of MSI in ASD
27
(Dawson & Watling, 2000). Differentiating between a sensory integration deficit
at the lower level versus difficulty processing and integrating social information is
crucial in order to ensure that research can help to inform clinical practice and
guide intervention.
The goal of the present study is to examine multisensory functioning at the
lower level of sensory processing in ASD by identifying whether or not these
individuals are susceptible to auditory-guided visual illusions. While some
research has been conducted using the flash-beep paradigm, these studies have
often focused on the temporal binding window in ASD, studied extremely highfunctioning individuals with very elevated IQ’s and have only studied adult ASD
populations. The aim for this study is to focus on lower level MSI by reducing the
complexity of task demands, by attempting to capture a more broad view of the
spectrum that is ASD and provide some insight into potential age differences in
MSI by investigating these processes in adolescents and adults.
Hypotheses
In light of the findings that lower level MSI may be intact in ASD, it is
hypothesized that performance on the flash-beep illusion task will be similar for
the ASD and TD groups. Specifically, it is expected that the ASD group be as
susceptible to both the fission and fusion illusion as the TD group with regard to
their accuracy in responding. It is also expected that individuals with ASD might
demonstrate slower reaction times (RTs) overall than the TD group as they have
been shown to have slower RT in response to reaction time tasks in the past
(Brandwein, et al., 2013; Schmitz, Daly, & Murphy, 2007; Wickelgren, 2005).
28
Furthermore, we will be analyzing the effect of age on performance to this task. In
light of findings by Innes-Brown et al. (2011) whereby children (aged 8-17) were
significantly more susceptible to fission illusions than adults, it is hypothesized
that a similar pattern of results will be found in both the ASD and comparison
groups.
Methods
Participants
ASD group. Twenty adolescents and adults with ASD (either diagnosed
with Autistic Disorder or Asperger’s Syndrome) were recruited from the Clinique
d’Évaluation des Troubles Envahissants du Développement (CETED) database, at
the Rivière-des-Prairies Hospital in Montreal. Before moving forward with
recruitment, ethics approval was applied for and obtained from the Research
Ethics Committee of the Rivière-des-Prairies Hospital. To facilitate recruitment, a
set of specific criteria was defined (e.g., age range between 13 and 17 for
adolescents and between 18 and 30 for adults; ASD diagnosis; FSIQ above 70)
and a list of potential participants was generated from the CETED database.
Individuals within this group were chosen based on their meeting diagnostic
criteria for ASD according to the Autism Diagnosis Interview-Revised (Lord,
Rutter, & Le Couteur, 1994) and the Autism Diagnosis Observation Schedule
(Lord, Cook, Leventhal, Amaral, 2000). Participants were then randomly selected
from the generated list and contacted by a research assistant who used a script
designed to explain the study and identify the presence of exclusionary criteria
(See Appendix A for the telephone recruitment script). Of the twenty ASD
29
participants, 4 had received diagnoses of Asperger’s syndrome and 16 were
diagnosed with Autism Spectrum Disorder.
In order to facilitate matching with the comparison group, and because the
task for this study required an ability to sustain attention and follow specific
instructions, only higher functioning participants with ASD were selected (i.e.,
Full Scale Weschler IQ scores greater than 70). Each participant had previously
been tested using the Weschler Intelligence Scale for Children (WISC-IV), the
Weschler Adult Intelligence Scale (WAIS-IV) or the Weschler Abbreviated Scale
of Intelligence (WASI-II). The overall average IQ of ASD participants was
102.95 (SD 13.71), with the average IQ for the adolescent ASD group being 101.5
(SD 15.26), and for the adult ASD group being 104.4 (SD 12.62). In addition,
due to the importance of visual and auditory information, participants had to have
normal or corrected to normal vision and no auditory problems. Participants were
asked about their vision and audition during recruitment and they also underwent
a visual acuity test prior to testing.
Due to the sex differences that exist in ASD (i.e., approximately 4.3:1 of
males to females; Fombonne, 2003), our sample consisted mostly of males, with
16 males (80%) and 4 females (20%). For the purpose of analyzing age
differences, the ASD group was evenly split into 10 adolescents between 13 and
17 (mean age 14.80; SD 1.48) and 10 adults ranging from 18 to 29 years old
(mean age 22.7; SD 3.27). Collapsing the adolescent and adult groups, the mean
age for the ASD group was 18.75 (SD 4.74).
Typically-developing comparison group. Performance of the ASD group
was compared to that of TD individuals. The TD participants were recruited from
30
the CETED database as well announcements made through the Perceptual
Neuroscience Laboratory for Autism and Development (PNLab). A semistructured interview conducted during recruitment allowed for the exclusion of
TD participants with: a history of learning disabilities; a familial history (1st
degree) of mood disorders, ASD or schizophrenia; defective vision or audition; as
well as those who were currently taking psychiatric medications or recreational
drugs. The TD participants, like the ASD participants, completed a test of visual
acuity prior to testing. Participants from both groups were matched as closely as
possible on gender, age and IQ, although due to the small sample size, there still
was some variability on these factors. The overall average IQ of TD participants
was 108.15 (SD 11.36), with the average IQ for the adolescent TD group being
105.1 (SD 10.70), and for the adult TD group being 111.2 (SD 11.72).
There were 18 males (90%) and 2 females (10%) in the TD group. Like
the ASD group, the comparison group was split into adolescents (mean age 14.5;
SD 1.58) and adults (mean age 23.4; SD 2.76). The overall average age for the TD
group was 18.95 (SD 5.06).
Testing location and procedure for participants. Participants were all
tested within one of the two satellite locations of the PNLab. Testing occurred
either in the auditory testing room of the Rivière-des-Prairies Hospital, which is
designed to diminish the presence of external light sources, or in a testing room
for the PNLab located at McGill University, which also created a darkened
environment void of external light sources. Testing in a darkened room was
necessary to ensure optimal perception of stimuli because the presence of external
light could impact performance on the experimental task. Upon arriving at the
31
testing session, participants were greeted by a research assistant who explained
the study and the procedure for the appointment, and answered any questions the
participant may have had. Every participant was asked to sign a consent form
outlining procedure, goals of the study, risks and benefits (see Appendix B for the
adult consent form and Appendix C for the consent form for minors). Participants
in both groups were given financial compensation for their time (15$/hour).
Apparatus
The flash-beep task was designed and presented using VPixx ™ software
and a MACPRO G4 computer, using an 18-inch Viewsonic E90FB .25 CRT
(1280 X 1024 pixels) screen with a refreshing rate of 75Hz. The mean luminance
of the monitor was set at 30.00 cd/m2 (u’ = 0.1912, v’ = 0.4456 in CIE color
space) where minimum and maximum luminance levels were 0.5 and 59.5 cd/m2,
respectively. Auditory stimuli were administered via the DataPixx™ data
acquisition box. This system allows for the production of sounds at precise
frequency and guarantees stability in the quality of auditory stimuli emitted. The
auditory stimuli were presented in dichotic listening at 65 db SPL (sound pressure
level), with Sennheiser HD280 headphones. Stability of auditory intensity and
visual luminance levels was ensured using a sonometer Quest 1100 and a CS-100
Minolta Chromameter, used for luminance/color reading and monitor gammacorrection.
Stimuli and Procedure
The described stimuli and procedure were largely based on those outlined
32
in the study by Shams et al. (2002) and in the study by Innes-Brown et al. (2011).
The visual stimulus was a white disk subtending 3° of visual angle and positioned
7.5° below a white fixation cross presented on a black background (see Figure 1
for an illustration of the stimuli). The fixation cross, which was constantly present
throughout the trials, was located 2.5° above the center of the screen. The duration
of presentation of the white disk (i.e., flash) was 12.5 milliseconds. On certain
trials, the flashes were paired with beeps that were presented at the same time.
The beeps consisted of a simple tone presented for the same duration of time as
the flash (12.5ms) through noise-cancelling headphones. Participants sat in a
comfortable armless chair, and viewing distance was set at 57cm from the eyes of
the participants to the centre of the screen.
Figure 1. Illustration of stimulus presentation for the flash-beep illusion task. The
fixation cross, which remains on the computer screen throughout the task, is
presented against a black background. A white disk (the visual stimulus) is
presented below the fixation cross and flashes once or twice in quick succession.
On every trial of the experiment, there were either one (1F) or two (2F)
flashes (F) presented and either zero (0B), one (1B), or two beeps (2B) presented
33
congruently in time. Therefore there are a total of six possible auditory-visual
combinations. The four non-illusion trials are 1F/0B, 1F/1B, 2F/0B, and 2F/2B,
because the auditory and visual information are not discordant lead to recognizing
the appropriate number of flashes; no illusory perception of the visual information
occurs. The fission illusion trial is the 1F/2B combination, and the fusion illusion
trial is the 2F/1B combination. On these illusion trials, the auditory information
drives the perception of the visual information. While only 1 flash is presented on
the fission illusion trial, the fact that it is paired with 2 beeps causes the
participant to believe 2 flashes were presented because the auditory information is
“fissuring” the perception of the visual information. Similarly, when 2 flashes are
paired with only 1 beep, there is a “fusion” of the visual information that occurs;
participants perceive only 1 flash when in actuality, 2 flashes were presented. For
trials in which there are multiple flashes or beeps (i.e., 1F/2B, 2F/0B, 2F/1B, or
2F/2B), the time delay between the first and second stimulus was set at 75 ms.
Trials each began with the presentation of the fixation cross, and
participants were instructed to press the space bar of a keyboard to activate the
start of each trial. Participants were instructed to always fixate their gaze on the
cross. The instruction given to the participants was that they count the number of
flashes that had appeared on each trial. They had to respond by pressing the “1”
button or the “2” button on the number pad located on the right side of the
keyboard. The participants were instructed to press the “1” button when they have
seen 1 flash and press the “2” button when they have seen 2 flashes. They were
also instructed ahead of time to make their best guess if they were unsure of the
number of flashes presented on any given trial.
34
The six trial types (i.e., 1F/0B, 1F/1B, 1F/2B, 2F/0B, 2F/1B, and 2F/2B)
were each presented 10 times in random order in a single testing block. There
were a total of six testing blocks, meaning that each trial type was presented 60
times total. Trials were separated into 6 testing blocks, each lasting approximately
2 minutes, in order to ensure that the participants did not become too tired or lose
focus. They were also encouraged to take breaks between testing blocks.
Furthermore, because each individual trial began with a bar-press, participants
could move through the blocks at their own pace and take a short break anytime
should they feel the need to do so without impacting the data. The accuracy of
their responses (i.e., pressing 1 when there was only one flash or 2 when there
were two flashes) as well as their reaction times was measured for each trial.
Results
Table 1 shows the means, standard deviations and ranges for demographic
information (i.e., sex, age, and IQ). T-tests results indicated that no significant
differences existed between the age or FSIQ of the ASD group and the TD control
group.
Table 1
Means, Standard Deviations, Ranges and Mean Comparisons of Participant
Variables by Group
ASD (n=20)
TD (n=20)
Male
16
18
Female
4
2
35
t
P
-0.129
0.898
-0.129
0.205
Sex
Chronological Age
Overall
M
18.75
18.95
SD
4.74
5.06
Range
13-29
13-28
Weschler FSIQ
M
102.95
108.10
SD
13.71
11.46
Range
79-120
86-125
Analysis of Accuracy
A mixed 2-way ANOVA (2x6) was used to determine whether differences
in accuracy on each of the six trial types existed between the two groups. The
ANOVA had a within-subjects factor of trial type (2F2B, 2F1B, 2F0B, 1F0B,
1F1B, 1F2B) and a between-subjects factor of group (ASD, Control). Accuracy
was measured as percentage of correct response (e.g., pressing “2” when two
flashes were shown) out of all possible responses for each trial type. Mauchly’s
test indicated that the assumption of sphericity had been violated
(χ2(14) = 134.64, p < .05), therefore degrees of freedom were corrected using
36
Greenhouse-Geisser estimates of sphericity (ε = 0.54).
The ANOVA revealed a main effect of trial type, F(2.72, 103.26) = 92.35,
p < .05, ηp2 = .011. Specifically, a Post hoc Bonferroni comparison determined
that accuracy for both groups was significantly lower for the 2F1B (Fusion) and
the 1F2B (Fission) trials than all other trial types, p < .05 (see Table 2 for mean
accuracy scores for each trial). In addition, the 2F2B trial was found to have
significantly higher accuracy scores than trials 2F0B and 1F0B, p < .05, and the
1F1B trial had significantly higher accuracy scores than the 2F0B trial, p < .05.
Table 2
Mean Accuracy Scores and Standard Errors for Each Trial Type Across Groups.
Trial Type
Means
Standard Error
2F2B
95.66
1.13
2F1B (Fusion)
59.79
4.66
2F0B
83.71
2.61
1F0B
86.54
2.47
1F1B
93.37
1.00
1F2B (Fission)
30.20
4.56
The analyses also revealed that there was no main effect of group, F(1, 38)
= 3.80, p > .05, ηp2 = .091. In other words, the overall accuracy scores of the
ASD group (mean overall accuracy of 71.07%) and the Control group (mean
overall accuracy of 78.69%), when collapsing across all trial types, did not differ.
Of particular interest is the finding that there existed a significant interaction
37
effect of group x trial type, F(2.71, 103.26) = 4.35, p < .05, ηp2 = .103. This result
indicates that differences existed between the ASD and Control groups with
regards to their performance on specific trial types (see Figure 2). Specifically,
using a Post hoc Bonferroni comparison, it was found that the groups had
significantly different accuracy scores on the 2F1B (fusion) trial and the 2F0B
trial. Whereas performance did not differ on the other four trial types, the ASD
group had significantly lower accuracy scores on the 2F1B and 2F0B trials (see
Table 3 for mean accuracy scores for group by trial).
Figure 2. Bar graph representing the difference in accuracy scores on each trial
type between the ASD and Control groups.
Table 3
Mean Accuracy Scores and Standard Errors for Each Trial Type Based on Group.
Group
Trial Type
Means
Standard Error
ASD
Control
38
2F2B
94.16
1.59
2F1B (Fusion)
45.75*
6.60
2F0B
77.50*
3.69
1F0B
86.00
3.49
1F1B
92.91
1.41
1F2B (Fission)
30.08
6.44
2F2B
97.16
1.59
2F1B (Fusion)
73.83*
6.60
2F0B
89.91*
3.69
1F0B
87.08
3.49
1F1B
93.83
1.41
1F2B (Fission)
30.33
6.44
Note. * = p<.05
Analysis of RT
Differences between groups on reaction time (RT) for the different trials
was assessed using a mixed 2-way ANOVA (2x6) with groups (ASD, Control) as
the between-subjects factor and trial type as the within-subjects factor. Reaction
time (measured in milliseconds) was defined as the time between presentation of
the stimuli and participant response (key press). Mauchly’s test of sphericity was
significant, indicating that the assumption of sphericity was violated, (χ2(14) =
80.12, p < .05). Accordingly, degrees of freedom were corrected using
Greenhouse-Geisser estimates of sphericity (ε = 0.50).
39
A main effect of trial type on reaction time was found, F(2.49, 94.64) =
17.44, p < .05, ηp2 = .32. A Post hoc Bonferroni comparison was conducted and
showed that when both groups are collapsed and reaction time for each trial is
compared, performance on the 2F2B trial is significantly faster (i.e., smaller
reaction times) than performance on every other trial. Furthermore, reaction time
on the 1F0B trial appears to be significantly slower than for 2F2B, 2F0B, and
1F1B (see Table 2 for mean reaction times for each trial).
Table 4
Mean Reaction Times and Standard Errors for Each Trial Type Across Groups.
Trial Type
Means
Standard Error
2F2B
.537
.02
2F1B (Fusion)
.637
.03
2F0B
.629
.02
1F0B
.678
.02
1F1B
.625
.02
1F2B (Fission)
.675
.03
Analyses also revealed a significant main effect of group, F(2.49, 94.64) =
17.44, p < .05, ηp2 = .32. This indicates that if we collapse performance across
all trial types, the ASD and Control groups had significantly different RT’s in
general. Specifically, the ASD group (M = .69ms) was found to be slower than the
Control group (M = .57ms) overall. There is also an interaction effect of group x
trial type for RT, F(2.49, 94.64) = 3.38, p < .05, ηp2 = .082. The results revealed
40
that the ASD and Control group had significantly different RT’s for every trial
except 1F0B (see Figure 3). In fact, the ASD group was significantly slower than
the Control group on most trials (see Table 5 for mean RT’s for each trial by
group). Moreover, when examining differences between the reaction times on
different trials within each group, it was found that performance on the 2F2B trial
was significantly better (faster reaction times) than all other trials for the ASD
group, p < .05. For the Control group, reaction times were also significantly faster
for the 2F2B trial than every other trial, p < .05, but they also had significantly
slower RT’s on the 1F0B trial, p < .05, than every other trial except for 1F2B.
Figure 3. Bar graph representing the difference in reaction times on each trial type
between the ASD and Control groups.
Table 5
Mean Reaction Times and Standard Errors of Each Trial Type by Group.
41
Group
Trial Type
Means
Standard Error
ASD
2F2B
.598*
.028
2F1B (Fusion)
.702*
.039
2F0B
.701*
.033
1F0B
.697
.029
1F1B
.669*
.026
1F2B (Fission)
.756*
.043
2F2B
.475*
.028
2F1B (Fusion)
.572*
.039
2F0B
.557*
.033
1F0B
.659
.029
1F1B
.581*
.026
1F2B (Fission)
.593*
.043
Control
Note. * = p<.05
Analysis of Age Effects on Accuracy and RT
Given that age effects have been shown in past with the flash-beep illusion
task (Innes-Brown, et al., 2011) and that our sample has a relative large age range,
a Pearson product-moment correlation coefficient was conducted to assess the
relationship between age and performance (accuracy and RT) on the illusion trials
for each group (ASD and Control). Results yielded no significant correlations for
age by performance on the illusion trials for the ASD group. In other words, age
was not significantly correlated with accuracy or RT on the illusion trials for the
42
ASD group (see Table 6). For the TD control group, a negative correlation was
found between age of the TD group and RT on the fusion illusion trial, r = -.47, p
< .05 (see Figure 4). There were no significant correlations between age and
accuracy on either illusion trial for the TD group or between age and RT on the
fission illusion trial.
Table 6
Correlation between chronological age and performance (Accuracy and RT) for
fission and fusion trials for both ASD and TD groups.
Accuracy
Reaction Time
2F1B-Fusion 1F2B-Fission
2F1B-Fusion
1F2B-Fission
Age - ASD group
r
.39
.42
.06
.33
p
.09
.07
.80
.15
r
.11
.13
-.47
-.10
p
.65
.57
.04*
.67
Age - TD group
Note. * = p <.05
eaction Time (ms)
Age x Fusion Trial RT (TD Control)
1
0.8
0.6
0.4
0.2
43
Figure 4. Scatterplot representing the significant correlation between age and RT
on the 2F1B fusion trial for the TD control group.
Discussion
The goal of the current study was to assess multisensory integration in
ASD for low-level information void of socio-communicative context using the
flash-beep paradigm (Innes-Brown, 2011; Shams et al., 2002), which assessed the
susceptibility to auditory-guided visual illusions. Based on previous research, we
hypothesized that the ASD and TD groups would be equally susceptible to the
fusion and fission illusions, that the ASD group may have slower reaction times
and that age effects would be present with regard to susceptibility to the illusions
for both groups. These findings would suggest intact MSI abilities in ASD in
contrast to the difficulty with integrating sensory information previously found in
ASD when tested using higher-level tasks and social stimuli (Brandwein et al.,
2013; Foxe & Molholm, 2009; Iarocci & McDonald, 2006; Mongillo et al., 2008).
44
Multisensory Facilitation
In line with our expectations, both groups were found to have significantly
diminished accuracy on the fusion (2F1B) and fission (1F2B) trials (i.e., increased
susceptibility), indicating that the task was functioning as expected. Furthermore,
the results of the ANOVA showed that there was significantly better accuracy for
both groups on the 2F2B as compared to the 2F0B and 1F0B trials, significantly
better accuracy on the 1F1B trial than the 2F0B, and a difference approaching
significance (p = 0.057) between the 1F1B and 1F0B trial. Taken together these
results can be explained by multisensory facilitation (Calvert & Thesen, 2004;
Collignon et al., 2012; Iarocci & McDonald, 2006). The 2F2B and 1F1B trials
involve multisensory facilitation (i.e., better responding to matching visual and
auditory stimuli presented congruently), whereas the 1F0B and 2F0B trials do not
have incongruent sensory information but neither do they offer the opportunity of
multisensory facilitation due to the lack of auditory information. The fact that all
participants performed with more accuracy on trials in which there was congruent
information from both sensory modalities indicates that both groups were
showing evidence of multisensory facilitation; the presence of congruent sensory
information from both the auditory and visual modality allowed the individuals
from both groups to respond more accurately.
With regard to reaction time, previous findings had shown that individuals
with ASD tend to have slower reaction times in response to sensory stimuli than
TD individuals (Brandwein, et al., 2013; Schmitz, Daly, & Murphy, 2007;
Wickelgren, 2005). Our findings are in line with previous findings that individuals
45
with ASD have slower reaction times to reaction time tasks than TD individuals.
However, both groups had faster reaction times on the 2F2B trial than all other
trials. This finding further supports the notion that there exists multisensory
facilitation in ASD in response to trials in which congruent auditory and visual
information is presented. Multisensory facilitation occurs in response to congruent
stimuli from multiple sensory modalities and leads to more efficient responding.
Thus, although the ASD group was significantly slower on most trials, they were
responding faster when the auditory and visual information was congruent,
demonstrating an effect of multisensory facilitation, although this effect was only
significant for the 2F2B trial and not the 1F1B trial. Collignon et al. (2012) did
not find any evidence of multisensory facilitation in their study of ASD
participants on a visual search task. It may be the case that multisensory
facilitation was not found on the visual search task because, while it still utilized
simple non-social stimuli, the task itself was more cognitively taxing and called
upon attention which is a higher order cognitive process. Perhaps only lower-level
non-social tasks, like the flash-beep paradigm, result in some facilitation in
individuals with ASD, and that when task demands become more complex (i.e.,
like in a visual search task) individuals with ASD begin to benefit less from the
congruent presentation of sensory information from different sensory modalities.
Susceptibility to the Fusion and Fission Illusions
Also, in line with our hypothesis, there was no main effect of group found
with regards to accuracy across all trials. This result suggests that individuals with
ASD complete the flash-beep task with similar levels of accuracy to TD
46
individuals. Previous research has shown that in TD populations, the fission
illusion is more robust than the fusion illusion (i.e., lower accuracy on fission
trials than fusion trials; Andersen, Tiippana, & Sams, 2004; Shams et al., 2002).
The current study replicated past findings and demonstrated that the TD group
had significantly lower accuracy on both the fusion and fission illusion trials as
compared to all four other trial types, but that susceptibility to the fission illusion
was stronger than to the fusion illusion.
The results of the present study also demonstrated that the ASD group, as
compared to the TD, was actually found to have significantly lower accuracy
levels on the fusion trial, but there was no difference between groups on the
fission illusion trial. The finding that the ASD group had significantly lower
accuracy on the fission trial than every other trial and that their levels of
susceptibility to this illusion did not differ from the TD group is line with our
hypothesis. In other words, the fission illusion appears to be as robust in
individuals with ASD and TD individuals. However, the finding that individuals
with ASD are actually significantly more susceptible to the fusion illusion is
particularly intriguing because it stands in stark contrast to the assertion that
individuals with ASD may not be integrating sensory information as much as TD
individuals.
The level of susceptibility to both illusions was not significantly different
in the ASD group, which indicates that the effect of both illusions is robust in this
population. A lower level of accuracy on an illusion trial is interpreted as meaning
that MSI is actually more automatic. Taken together, the results of the analysis of
accuracy demonstrate that individuals with ASD are integrating sensory
47
information to the same degree as TD individuals and may in fact even be
integrating sensory information more automatically than TD individuals (as is
evidenced by their increased susceptibility to the fusion illusion). These findings
provide further support to the growing body of lower level MSI research in ASD
that is beginning to suggest that there is no evidence for impaired integration of
lower level stimuli in ASD (Foss-Feig, et al., 2010; Keane, et al., 2010 Kwakye,
Foss-Feig, Cascio, Stone, & Wallace, 2011; van der Smagt, et al., 2007).
The study conducted by Innes-Brown et al. (2011) found that children
were more susceptible to both the fusion and fission illusions than adults. They
suggested that this difference was due to a more automatic, but less selective
integration of sensory information in children. The idea behind this is that
children may not yet have “fine-tuned” their ability to integrate sensory
information; their visual perception is being altered more automatically and more
often by incongruent auditory information than is the case with older individuals.
Our findings that individuals with ASD are significantly more susceptible to the
fusion illusion than TD individuals may also be indicative that multisensory
integration at the lower-level is somewhat more automatic but less selective in
ASD. This interpretation is consistent with previous findings that individuals with
ASD have a larger temporal binding window than TD individuals (i.e., they
integrate sensory information into a whole over a longer temporal gap of stimulus
presentation; Foss-Feig, et al., 2010; Kwakye et al., 2011; Woynaroski et al.,
2013). If individuals with ASD were not integrating sensory information, they
would not be susceptible to the illusions of the flash-beep task and would even
have a smaller temporal binding window (i.e., they would not perceive as
48
occurring together in time two events that were separated by even a very small
time gap). Our findings taken together with findings from studies investigating the
temporal binding window suggest that individuals with ASD do not appear to
have an inability to integrate sensory information from different modalities but
that they may simply be integrating the information in a different, possibly more
automatic and less selective manner.
Age Effects
No age effects in relation to performance on illusion trials were found
within the ASD group. For the control group, a slight negative correlation was
found between chronological age and RT on the fusion illusion task (i.e., as age
increased, RT for the fusion illusion task became faster). The lack of significant
age effects on accuracy for both groups is inconsistent to the hypothesis that
younger individuals would be more susceptible to illusions and that susceptibility
would decrease with age. Innes-Brown et al., (2011) had found that TD children
were significantly more susceptible to both illusions than were TD adults.
However, the lack of consistency between the current findings and past findings
of age effects on illusion susceptibility is likely due to both our small sample size
and the fact that Innes-Brown et al. had tested children as young as 8 and we only
tested adolescents as young as 13. In order to truly look at developmental effects
throughout a wider age range, a larger sample size is needed, an issue which is
addressed in the future directions section and which we, as a research group, plan
to attend to in the future.
49
Clinical Implications
Sensory abnormalities are quite prevalent in ASD and the presence of
impaired MSI has been hypothesized to underlie the core features of ASD
(Dawson & Watling, 2000). Our findings add to the growing body of literature
that suggests MSI impairments may solely be present when processing sensory
information that involves social or communicative components. At the treatment
level, Sensory Integration Therapies (SIT) have been very popular and are
routinely implemented with children with ASD despite the lack of evidence for
their efficacy (Baranek, 2002; Dawson & Watling, 2000; Lang et al., 2012).
Sensory Integration Therapies (SIT) were developed on the notion that addressing
sensory abnormalities could lead to the reduction of stereotyped and repetitive
behaviours in ASD. Children seek out sensory activities that are thought to allow
them to better organize and integrate sensory information, which in turn would
lead to improved perceptual abilities and ultimately more adaptive behavioural
functioning (Baranek, 2002). Dawson and Watling (2000) as well as Baranek
(2002) reviewed the available evidence for the efficacy of SIT’s to improve
functioning in ASD and determined that there is a relative lack of evidence for the
efficacy of SIT’s but that it was difficult to make any firm conclusions due to the
lack of relevant research. Lang et al. (2012) conducted a similar review more
recently and determined that, while more research would help to better understand
the efficacy of SIT’s, these forms of therapy are not effective and there exists a
disconnect between research and practice in the field of sensory processing and
integration in ASD. Although the current study cannot directly speak to the
50
efficacy of SIT’s, the finding that MSI appears to function largely normally at the
lower level in ASD would call into question the rationale for SIT’s. If in fact the
supposed impairment in MSI is more of an issue with processing social
information rather than an impairment at the lower level of processing, SIT’s may
be attempting to target a problem that does not exist.
Further investigation is needed to fully understand the sensory processing
and sensory integration profile of individuals with ASD, but the current pattern of
findings in the literature would suggest that individuals with ASD may benefit
more from treatment efforts that focus on developing social and communicative
abilities (e.g., integrating speech, gesture and lip-reading, attending to social cues)
rather than those that focus on developing sensory integration abilities.
Limitations & Future Directions
Considerations should be made with regard to the interpretation of the
results of this study. One of the major limitations is the small sample size, 20
ASD and 20 TD participants. The size of the sample limits the interpretation and
generalizability of the results, particularly within a developmental context. Future
studies would need to obtain larger sample sizes to provide greater statistical
power.
Another limitation with respect to interpretation of age effects is the lack
of a child group. The lack of an age effect on the accuracy of illusion trials may
be due in part to the inability to compare younger children to adults. Increasing
sample size and adding children (e.g., 6-12) to the ASD and TD groups would
allow for the further investigation of developmental trajectories in multisensory
51
processing at the lower level. To our knowledge, no study has yet compared
performance on lower level MSI tasks across age groups to investigate
developmental trends.
Another major limitation of our study is the use of only higher-functioning
individuals in the ASD group. Results of the current study may not be
generalizable to all individuals with ASD, a highly variable spectrum of symptom
severity. Due to the need for sustained attention and following specific rules, only
higher-functioning individuals were tested, and thus results may only generalize
to higher-functioning individuals with ASD. Future studies may want to modify
task demands and shorten testing time to allow for the testing of lowerfunctioning ASD individuals on lower level multisensory tasks such as the flashbeep task used in this study. Every study using lower level stimuli to assess MSI
that has been conducted to date to our knowledge has solely tested highfunctioning ASD individuals. Due to the fact the lower-functioning individuals
with ASD are also affected by sensory abnormalities, there is a need to assess
MSI functioning across the spectrum of ASD. It may be possible to include lower
functioning ASD individuals in future research by using an electrophysiological
approach on a more passive task. For instance, individuals could be presented
with simple stimuli (i.e., auditory stimulus alone, visual stimulus alone, and
audiovisual stimuli presented together) and their brain activity could be measured
to determine whether there exist differences in sensory processing and integration
at the neural level.
The current study only assesses MSI functioning using lower level stimuli.
Future investigations might be strengthened by having the same participants
52
complete similar tasks that use socio-communicative stimuli as well as lower level
stimuli. Our group is currently investigating this issue more broadly, having
examined multisensory integration using more complex higher-level tasks that use
socio-communicative stimuli (Charbonneau et al., 2013), tasks of mid-level
complexity (i.e., that tap into attentional processes) with non-social stimuli
(Collignon et al., 2012), and lower-level perceptual tasks with non-social stimuli
(the current study). The next step would be to test the same participants on this
range of multisensory integration tasks to truly parse apart whether the MSI
difficulties that have previously been found in ASD are related to information that
is socio-communicative in nature or related to task complexity.
Finally, while the current study provides an indication of MSI functioning
at the behavioral level, a future direction for studies investigating MSI in ASD
could involve looking at the relationship between behavioral manifestations of
MSI abilities and the neural networks underlying these processes. Some studies
have already begun to investigate MSI in ASD using neuroimaging methods (e.g.,
EEG, fMRI) but additional research is needed to fully understand the neural
mechanisms that underlie sensory processing and integration in ASD in order to
better inform treatment of this population and possibly to aid in early
identification (Brandwein et al., 2013; Maekawa, 2011; Magnée et al., 2008).
Conclusion & Summary
The current study provides further support for the growing body of
literature that suggests that MSI may be intact at the lower level in individuals
with ASD. The goal was to investigate MSI functioning via auditory-guided
53
visual illusions and it was found that individuals with ASD are equally susceptible
to the fission illusion as the TD group, suggesting intact MSI at the lower level.
Moreover, the ASD was found to be even more susceptible to the fusion illusion
when compared to TD participants indicating less selective but more automatic
MSI than TD individuals. These findings are inconsistent with the assumption that
individuals with ASD have weak central coherence and do not integrate sensory
information into coherent wholes. In fact, their increased susceptibility to the
fusion illusion indicates that, if anything, they may be over-integrating sensory
information. The results of this study may be more in line with the hypothesis of
an expanded temporal binding window in ASD, which explains that individuals
with ASD integrate information from different sensory modalities but do so less
selectively and over a wider temporal gap. These findings, combined with those
of past studies on MSI in ASD, provide a better understanding of the way in
which individuals with ASD integrate sensory information and can ultimately
help inform treatment strategies for individuals with ASD. The future directions
outlined in this study will hopefully provide additional, much-needed information
about the way individuals with ASD perceive sensory information and the impact
that sensory processing and integration has on the way in which these individuals
interact with their environment.
54
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Appendix A
Telephone Script for Participant Recruitment
« Bonjour, je m’appelle … … , je suis assistant(e) de recherche au laboratoire de
recherche du Dr Bertone à l’hôpital Rivière-des-Prairies. Je vous appelle afin de
vous demander si vous seriez intéressé et disponible pour participer à une étude.
Le titre de l’étude est : L’Évaluation de l’intégration multisensorielle et de la
sensibilité aux illusions visuelles chez les individus atteints d’autisme.
« Votre participation consistera à effectuer diverses tâches dans lesquelles vous
aurez à détecter différents types de stimuli qui vous seront présentés. Vous devrez
participer à une session d’environ 2 heures et demi afin de compléter les tâches.
Des stimuli visuels seront présentés à l’écran d’ordinateur et vous devrez indiquer
si vous détectés un ou plusieurs flashs.
Vous n’avez aucun avantage direct à participer à cette étude à part le fait
de faire avancer les connaissances scientifiques sur l’autisme. Il n’existe pas de
risques prévisibles liés à votre participation, mis à part le temps que cela vous
prendra pour effectuer les tâches et votre déplacement.
La compensation pour l’étude est de 15$ de l’heure. Il vous est possible
d’abandonner l’étude à tout moment.»
Si la personne est intéressée, vérifier si elle répond aux critères d’inclusion :
« J’aurais quelques questions à vous poser avant de confirmer votre participation
à l’étude. Avez-vous des problèmes spécifiques de vision? Portez-vous des
lunettes ou des verres de contact qui corrigent ces problèmes de vision?
Prenez actuellement des médicaments présentement? Si oui, quel type? »
Si la personne répond aux critères :
« Quand seriez-vous disponibles pour participer à l’étude? »
Fixer le rendez-vous.
« Parfait, je viendrai vous chercher à l’accueil du l’Hôpital Rivière des Prairies, à
l’heure et au jour fixé, je vous laisse le numéro où me joindre d’ici là. Le
formulaire de consentement sera expliqué et signé sur place.
S’il vous plaît, il est important de ne consommer ni alcool ni drogues dans
les jours qui précèdent le rendez-vous.
Avez-vous des questions? Si vous
souhaitez me rejoindre, vous pouvez me contacter au (numéro téléphone). Merci
beaucoup.»
65
Appendix B
Consent Form – Adult Participants
FORMULAIRE D’INFORMATION ET DE CONSENTEMENT
(Participants majeurs)
1. Titre du projet, nom des chercheurs et affiliation
L’évaluation de l’intégration multisensorielle chez les individus atteints d’autisme.
Chercheurs principaux
Vanessa Bao, B.A.
Étudiante à la maitrise en School/Applied Child Psychology
Université McGill
Co-chercheurs
Armando Bertone, Ph.D.
Professeur adjoint, Université McGill
Chercheur, Hôpital Rivière-des-Prairies
Directeur, Perceptual Neuroscience Lab (PNLab) for Autism and
Development
2. Description du projet
Cette étude vise à déterminer si les personnes atteintes d’autisme ont des
difficultés spécifiques dans l’intégration d’informations. Ceci sera évalué à l’aide
d’une tâche faite à l’ordinateur en comparant les capacités pour l’intégration
d’information provenant de différentes modalités sensorielles (auditives et
visuelles) chez les individus atteints d’autisme avec celles d’un groupe de
participants non-autistes.
3. Procédures de l’étude
Je devrai participer à une session d’environ 1h½, afin de compléter deux tâches.
Pour la première tâche, ma participation consiste à détecter un son, une image
présentée sur un écran d’ordinateur ou parfois les deux en même temps. Pour la
deuxième tâche, ma participation consiste à discerner si j’ai perçu un ou deux
flashs présentés sur un écran d’ordinateur. Cette tâche sera effectuée au
Laboratoire de Neuroscience de la Perception pour l’autisme et les conditions du
développement de l’Hôpital Rivière-des-Prairies.
4. Avantages et bénéfices pour le sujet
Il n’y a aucun avantage découlant de ma participation à cette étude, outre le fait de
contribuer à l’avancement des connaissances scientifiques dans ce domaine de
recherche.
5. Indemnité compensatoire
Suite à cette expérience, une indemnité compensatoire de 15$ par heure me sera
remise.
66
6. Inconvénients et risques
Un inconvénient est le temps pris pour me rendre à l’Hôpital Rivière des Prairies,
ou l’étude s’effectue, ainsi que le temps que je vais mettre pour compléter les
tâches. Aucun risque connu n’est relié aux expériences auxquelles je vais
participer. Des mesures seront prises afin de palier aux éventuels inconvénients
qui peuvent êtres entraînés par la répétition de stimuli soit la fatigue, l’inconfort
relié à l’immobilité et à l’attention soutenue. En effet, la présentation des stimuli
sera régulièrement interrompue, me permettant ainsi de relaxer légèrement.
7. Modalités prévues en matière de confidentialité
Les informations qui me concernent dans le cadre de ce projet demeureront
confidentielles. Un code chiffré sera utilisé pour remplacer mon nom de sorte
qu’aucun membre de l’équipe autre que les chercheurs impliqués dans l’étude
(mentionnés plus haut), ne puisse m’identifier. Les données obtenues au cours de
ce projet seront donc codées, mais non anonymes. Un code sera utilisé lors de la
publication de l’étude et dans aucun cas mon nom ne sera divulgué. Les données
nominatives ne seront pas conservées. Seules les données brutes le seront. Ces
données seront conservées pour une période de dix ans, car elles sont nécessaires
aux vérifications suite à la publication. Mes informations personnelles contenues
dans la base de données de la Clinique de l’autisme de l’Hôpital Rivière-desPrairies pourront êtres consultés dans le cadre de cette recherche, et les résultats
de la présente recherche pourront y êtres transférés. Il est possible que les
chercheurs doivent permettre l’accès aux dossiers de recherche au comité
d’éthique de la recherche de HRDP et aux organismes subventionnaires de la
recherche à des fins de vérification ou de gestion de la recherche. Tous adhèrent à
une politique de stricte confidentialité.
8. Clause de responsabilité
S’il survient un incident suite à ma participation à cette étude, je pourrai faire
valoir tous les recours légaux garantis par les lois en vigueur au Québec, sans que
cela n’affecte les soins qui me sont prodigués. Ma participation ne libère ni les
chercheurs ni l’établissement de leurs responsabilités civiles et professionnelles.
9. Liberté de participation et droit de retrait
Ma participation à cette étude est tout à fait volontaire. Ainsi, je suis libre
d’accepter ou de refuser d’y participer. Mon refus ne va pas nuire à mes relations
avec mon médecin ou avec les autres intervenants si je suis un patient à l’Hôpital
Rivière des Prairies. Je suis également libre de me retirer de cette étude en tout
temps. Toute nouvelle connaissance acquise au cours du processus
d’expérimentation pouvant affecter ma décision d’y participer me sera
communiquée dans les plus brefs délais. Mes données seront détruites au cas où je
déciderais de ne pas compléter les tâches.
10. Nom des personnes-ressources
Pour de plus amples renseignements au sujet de ce projet de recherche ou pour
aviser de mon retrait, je pourrai contacter le chercheur principal, Armando
67
Bertone, au 514-323-7260, poste 4571. Pour formuler une plainte, des
commentaires ou pour des questions concernant mes droits en tant que participant,
je pourrai communiquer avec la Commissaire locale aux plaintes et à la qualité
des services de l’Hôpital Rivière-des-Prairies, Mme Hélène Bousquet, au (514)
323-7260 poste, 2154.
11. Formule d’adhésion et signatures
J’ai lu et compris le contenu du présent formulaire. Je certifie que le contenu de ce
formulaire m’a également été expliqué verbalement. J’ai eu l’occasion de poser
toutes mes questions et on y a répondu de façon satisfaisante. Je sais que je suis
libre de participer au projet et que je demeure libre de m’en retirer en tout temps,
par avis verbal, sans que cela n’affecte la qualité de mes traitements, de mes soins
futurs et des rapports avec mon médecin ou avec le centre hospitalier si je suis
patient de l’Hôpital Rivière-des-Prairies. Je certifie que l’on m’a laissé le temps
voulu pour prendre ma décision et j’ai pris cette décision sans contrainte ni
pression de qui que ce soit. Je comprends que je recevrai une copie du présent
formulaire. Je consens à participer à ce projet de recherche.
_______________________
Nom du sujet en majuscules
____________________
Signature du sujet
____________
Date
12. Formule d’engagement du chercheur
Je certifie avoir expliqué au signataire les termes du présent formulaire de
consentement et avoir répondu à ses questions. Je certifie également lui avoir
clairement indiqué qu’il est libre de mettre un terme à l’expérimentation à tout
moment et que je lui remettrai une copie signée et datée du présent formulaire de
consentement.
_______________________
____________________
Nom du chercheur en majuscules Signature du chercheur
____________
Date
13. Informations de type administratif
Le formulaire original sera inséré à mon dossier médical (s’il y a lieu). Une copie
sera insérée dans le dossier de recherche et une autre copie me sera remise. Le
projet de recherche et le présent formulaire de consentement ont été approuvés par
le comité d’éthique de la recherche de l’Hôpital Rivière-des-Prairies.
68
Appendix C
Consent Form – Child & Adolescent Participants
FORMULAIRE D’INFORMATION ET DE CONSENTEMENT
(Participants mineurs)
1. Titre du projet, nom des chercheurs et affiliation
L’évaluation de l’intégration multisensorielle chez les individus atteints d’autisme.
Chercheurs principaux
Vanessa Bao, B.A.
Étudiante à la maitrise en School/Applied Child Psychology
Université McGill
Co-chercheurs
Armando Bertone, Ph.D.
Professeur adjoint, Université McGill
Chercheur, Hôpital Rivière-des-Prairies
Directeur, Perceptual Neuroscience Lab (PNLab) for Autism and
Development
2. Description du projet
Cette étude vise à déterminer si les personnes atteintes d’autisme ont des
difficultés spécifiques dans l’intégration d’informations. Ceci sera évalué à l’aide
d’une tâche faite à l’ordinateur en comparant les capacités pour l’intégration
d’information provenant de différentes modalités sensorielles (auditives et
visuelles) chez les individus atteints d’autisme avec celles d’un groupe de
participants non-autistes.
3. Procédures de l’étude
Mon enfant devra participer à une session d’environ 1h½, afin de compléter deux
tâches. Pour la première tâche, sa participation consiste à détecter un son, une
image présentée sur un écran d’ordinateur ou parfois les deux en même temps.
Pour la deuxième tâche, sa participation consiste à discerner s’il a perçu un ou
deux flashs présentés sur un écran d’ordinateur. Mon enfant va effectuer ces
tâches au Laboratoire de Neuroscience en Perception, à l’Hôpital Rivière-DesPrairies.
4. Avantages et bénéfices pour le sujet
Il n’y a aucun avantage découlant de sa participation à cette étude, outre le fait de
contribuer à l’avancement des connaissances scientifiques dans ce domaine de
recherche.
5. Indemnité compensatoire
Suite à cette expérience, une compensation financière de 15$ par heure sera
remise à mon enfant.
6. Inconvénients et risques
69
Un inconvénient est le temps pris pour me rendre à l’Hôpital Rivière des Prairies
avec mon enfant, ou l’étude s’effectue, ainsi que le temps mis par mon enfant
pour compléter les tâches. Aucun risque connu n’est relié aux expériences
auxquelles mon enfant va participer. Des mesures seront prises afin de palier aux
éventuels inconvénients qui peuvent êtres entraînés par la répétition de stimuli soit
la fatigue, l’inconfort relié à l’immobilité et à l’attention soutenue. En effet, la
présentation des stimuli sera régulièrement interrompue, permettant ainsi à mon
enfant de relaxer légèrement.
7. Modalités prévues en matière de confidentialité
Les informations qui concernent mon enfant dans le cadre de ce projet
demeureront confidentielles. Un code chiffré sera utilisé pour remplacer son nom
de sorte qu’aucun membre de l’équipe autre que les chercheurs impliqués dans
l’étude (mentionnés plus haut), ne puisse l’identifier. Les données obtenues au
cours de ce projet seront donc codées, mais non anonymes. Un code sera utilisé
lors de la publication de l’étude et dans aucun cas son nom ne sera divulgué. Les
données nominatives ne seront pas conservées. Seules les données brutes le seront.
Ces données seront conservées pour une période de dix ans, car elles sont
nécessaires aux vérifications suite à la publication. Les informations personnelles
de mon enfant contenues dans la base de données de la Clinique de l’autisme de
l’Hôpital Rivière-des-Prairies pourront êtres consultés dans le cadre de cette
recherche, et les résultats de la présente recherche pourront y êtres transférés. Il
est possible que les chercheurs doivent permettre l’accès aux dossiers de
recherche au comité d’éthique de la recherche de HRDP et aux organismes
subventionnaires de la recherche à des fins de vérification ou de gestion de la
recherche. Tous adhèrent à une politique de stricte confidentialité.
8. Clause de responsabilité
S’il survient un incident suite à la participation de mon enfant à cette étude, je
pourrai faire valoir tous les recours légaux garantis par les lois en vigueur au
Québec, sans que cela n’affecte les soins qui lui sont prodigués. Sa participation
ne libère ni les chercheurs ni l’établissement de leurs responsabilités civiles et
professionnelles.
9. Liberté de participation et droit de retrait
La participation de mon enfant à cette étude est tout à fait volontaire. Ainsi, il est
libre d’accepter ou de refuser d’y participer. Le refus de mon enfant ne va pas
nuire à ses relations avec son médecin ou avec les autres intervenants s’il est un
patient à l’Hôpital Rivière des Prairies. Il est libre de se retirer de cette étude en
tout temps. Je suis également libre d’accepter ou de refuser que mon enfant
participe à cette étude et je peux l’en retirer en tout temps, aux mêmes conditions.
Toute nouvelle connaissance acquise au cours du processus d’expérimentation
pouvant affecter sa décision d’y participer me sera communiquée dans les plus
brefs délais. Les données de mon enfant seront détruites au cas où il déciderait de
ne pas compléter les tâches.
10. Nom des personnes-ressources
70
Pour de plus amples renseignements au sujet de ce projet de recherche où pour
aviser de mon retrait, je pourrai contacter le chercheur principal, Armando
Bertone, au 514-323-7260, poste 4571. Pour formuler une plainte, des
commentaires ou pour des questions concernant mes droits en tant que participant,
je pourrai communiquer avec la Commissaire locale aux plaintes et à la qualité
des services de l’Hôpital Rivière-des-Prairies, Mme Hélène Bousquet, au (514)
323-7260 poste, 2154.
11. Formule d’adhésion et signatures
J’ai lu et compris le contenu du présent formulaire. Je certifie que le contenu de ce
formulaire m’a également été expliqué verbalement. J’ai eu l’occasion de poser
toutes mes questions et on y a répondu de façon satisfaisante. Je sais que mon
enfant est libre de participer au projet et qu’il demeure libre de s’en retirer en tout
temps, par avis verbal, sans que cela n’affecte la qualité de ses traitements, de ses
soins futurs et des rapports avec son médecin ou avec le centre hospitalier, si mon
enfant est un patient de l’Hôpital Rivière-des-Prairies. Je demeure aussi libre de
l’en retirer à tout moment aux mêmes conditions. Je certifie que j’ai eu
suffisamment de temps pour prendre la décision et que j’ai pris cette décision sans
contrainte ni pression de qui que ce soit. Je certifie que le projet a été expliqué à
mon enfant dans la mesure du possible et qu’il accepte d’y participer sans
contrainte ni pression. Je comprends que je recevrai une copie du présent
formulaire. Je consens à ce que mon enfant participe à ce projet de recherche.
_______________________
Nom du représentant légal
____________________
Signature du représentant légal
____________
Date
____________________
Signature du sujet
____________
Date
Assentiment du mineur
_______________________
Nom du sujet en majuscules
12. Formule d’engagement du chercheur
Je certifie avoir expliqué aux signataires les termes du présent formulaire de
consentement et avoir répondu à leurs questions. Je certifie également leur avoir
clairement indiqué qu’ils sont libres de mettre un terme à l’expérimentation à tout
moment et que je leur remettrai une copie signée et datée du présent formulaire de
consentement.
_______________________
____________________
Nom du chercheur en majuscules Signature du chercheur
____________
Date
13. Informations de type administratif
Le formulaire original sera inséré au dossier médical de mon enfant (s’il y a lieu).
Une copie sera insérée dans le dossier de recherche et une autre copie me sera
remise. Le projet de recherche et le présent formulaire de consentement ont été
approuvés par le comité d’éthique de la recherche de l’Hôpital Rivière-desPrairies.

Multisensory Integration in Autism Spectrum Disorders: Investigating

Transcription

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