The Clarity Chair Literature Review

Based on the following literature review, it is plausible to assume that correcting or improving the sensory systems that include sensory-motor, auditory, visual, vestibular and kinesthetic, could lead to an improvement or reversal in the symptoms of Dementia and/or Alzheimer’s Disease:

Sensori-motor/Sensory Integration references

Journal of Neural TransmissionFebruary 2010, Volume 117, Issue 2, pp 217-225

Somatosensory responses in normal aging, mild cognitive impairment, and Alzheimer’s disease.  Julia M. StephenRebecca MontañoChristopher H. DonahueJohn C. AdairJanice KnoefelClifford QuallsBlaine HartDoug RankenCheryl J. Aine

Abstract: As a part of a larger study of normal aging and Alzheimer’s disease (AD), which included patients with mild cognitive impairment (MCI), we investigated the response to median nerve stimulation in primary and secondary somatosensory areas. We hypothesized that the somatosensory response would be relatively spared given the reported late involvement of sensory areas in the progression of AD. We applied brief pulses of electric current to left and right median nerves to test the somatosensory response in normal elderly (NE), MCI, and AD. MEG responses were measured and were analyzed with a semi-automated source localization algorithm to characterize source locations and timecourses. We found an overall difference in the amplitude of the response of the primary somatosensory source (SI) based on diagnosis. Across the first three peaks of the SI response, the MCI patients exhibited a larger amplitude response than the NE and AD groups (P < 0.03). Additional relationships between neuropsychological measures and SI amplitude were also determined. There was no significant difference in amplitude for the contralateral secondary somatosensory source across diagnostic category. These results suggest that somatosensory cortex is affected early in the progression of AD and may have some consequence on behavioral and functional measures.


Auditory References

Central Auditory Dysfunction May Precede the Onset of Clinical Dementia in People with Probable Alzheimer’s Disease   George A. Gates MD1, Alexa Beiser PhD2, Thomas S. Rees PhD1, Ralph B. D’Agostino PhD3, Philip A. Wolf MD4 Journal of the American Geriatrics Society  Volume 50Issue 3pages 482–488March 2002

OBJECTIVES: To document the prognostic significance of a central auditory speech-processing deficit for the subsequent onset of probable Alzheimer’s disease.

RESULTS: Forty subjects (5.4%) received a diagnosis of probable Alzheimer’s disease during an average of 8.4 years (range 3–12) of follow-up; seven (17.5%) of these had a central auditory speech-processing deficit. The presence of a central auditory speech-processing deficit had an age-adjusted risk ratio for probable Alzheimer’s disease of 10.8 (95% CI = 4.6–25.2). A central auditory speech-processing deficit had a positive predictive value for subsequent probable Alzheimer’s disease of 47% but the sensitivity was only 17.5%.

CONCLUSION: Central auditory speech-processing deficits may be an early manifestation of probable Alzheimer’s disease and may precede the onset of dementia diagnosis by many years.

American Academy of Neurology; Central auditory function in Alzheimer’s disease  Alison M. GrimesCheryl L. GradyNorman L. FosterTrey Sunderland and Nicholas J. Patronas   Author Affiliations: Clinical Center (Ms. Grimes and Dr. Patronas), The National Institutes of Health, The National Institute on Aging (Dr. Grady), The National Institute of Neurological and Communicative Disorders and Stroke (Dr. Foster), and The National Institute of Mental Health (Dr. Sunderland). Bethesda, MD.

ABSTRACT: The central auditory (dichotic) function of 38 patients with Alzheimer’s disease was found to be significantly impaired when compared with a control group. Significant relationships were observed between dichotic scores and intelligence quotient, cortical atrophy in the temporal lobes, and cerebral glucose metabolism in the left temporal lobe. Comparing atrophy and glucose metabolism in the temporal lobes, we observed contralateral ear effects in dichotic performance as well as an interaction of asymmetry of atrophy with dichotic performance, consistent with previous models of dichotic listening in other forms of temporal lobe pathology.


Visual References

Visual dysfunction in Alzheimer’s disease: Relation to normal aging; Dr Alice Cronin-Golomb PhD1,*, Suzanne Corki



A Multi-Sensory, Automated and Accelerated
Sensory Integration Program
The Research
Below are several published research reports that document the efficacy of a
singular program such as auditory therapy or visual therapy alone as well as the
use of multi-sensory programs using one or more sensory programs together.
This is only a sample of the volumes of research that has been done.
In the real world, outside the therapy center, people use all their senses at one
time to perceive and interact in their environment, not just one sense at a
time. For example, it would not be very effective to try to learn to ride a bicycle
blindfolded. A person uses their sense of sight, sound, touch and balance to
learn and use this skill. The more of our senses we use and the more they
function together is what enhances the learning process. That is why training
multi-senses at the same time can not only help to develop each sense but also
train them to work together more optimally. A better integration of the senses can
help lay down a fundamental foundation from which awareness, perception,
reasoning, judgment and knowledge can develop and grow.
TheThe Clairity Chair not only combines and targets five important senses at one
time, auditory (sound), visual (sight), tactile (touch), vestibular (movement and
balance sense) and proprioception (perception of movement and spatial
orientation), but it does it using an automated system that results in faster, more
effective and consistent training that is passive, requiring no effort on the part of
the client. In the new technical age of computers and digital programs, we have
taken sensory integration to this new level of training which is still firmly based on
decades of solid published research and results as well as five years of clinical
results on TheThe Clairity Chair itself.

Multisensory integration of cross-modal stimulus combinations yielded responses
that were significantly greater than those evoked by the best component
stimulus. J Neurophysiol 97: 3193–3205, 2007. doi:10.1152/jn.00018.2007.
Multisensory Versus Unisensory Integration: Contrasting Modes in the Superior
Colliculus, Juan Carlos Alvarado, J. William Vaughan, Terrence R. Stanford, and
Barry E. Stein
Department of Neurobiology and Anatomy, Wake Forest University School of
Medicine, Winston-Salem, North Carolina

When sound and touch were activated simultaneously, the activation of the
auditory cortex was strongest. Auditory information in conjunction with tactile
input assists with making tactile decisions. Tactile and auditory stimulation
simultaneously and individually may positively impact neuroplastic changes in
individuals with neurological deficits or impairments. Used singularly, sound
produced greater brain activation than touch. When both tactile and auditory
stimuli were conveyed simultaneously, the response was more intense.
Differences between sound and touch verses a combination of the two stimuli
were significant. Again, the combined stimuli were most significant. Kayser C,
Petkov CI, Augath M, Logothetis NK. Integration of touch and sound in the
auditory cortex. Neuron. 2005;48:373-384.3
Kayser C, Petkov C, Augath M, Logothetis N. Integration of touch and sound in
the auditory cortex. Neuron. 2005;48:373-384.


The sensory integration approach is effective in reducing self-stimulating
behaviors, which interfere with the ability to participate in more functional
activities. Smith, S. A., Press, B., Koenig, K. P., & Kinnealey, M. (2005). Effects
of sensory integration intervention on self-stimulating and self-injurious
behaviors. American Journal of Occupational Therapy, 59, 418–425.


Compared to the normal control group, the children with ADHD showed abnormal
functional activity in several regions of the brain involved in the processing of
visual attention information. The researchers also found that communication
among the brain regions within this visual attention-processing pathway was
disrupted in the children with ADHD. Functional brain pathways disrupted in
children with ADHD November 30, 2011, Radiological Society of North America


Dyslexic children seem to have some highly specific visual deficits in processing
moving stimuli.
Clinical Neurophysiology 115 (2004) 90–96 Visual information processing in
dyslexic children, P. Scheuerpfluga,*, E. Plumea, V. Vettera, G. Schulte-
Koerneb, W. Deimelb, J. Bartlingb, H. Remschmidtb, A. Warnkea Department of
Child and Adolescent Psychiatry, University of Wuerzburg, Fuechsleinstrasse 15,
97080 Wuerzburg, Germany bDepartment of Child and Adolescent Psychiatry,
University of Marburg, Hans-Sachs-Strasse 6, 35039 Marburg, Germany
Accepted 28 July 2003


Neural Plasticity Following Auditory Training in Children with Learning Problem,
Hayes, E.A., Warrier, C.M., Nicol, T.G., Zecker, S.G., & Kraus, N. (2003). Neural
plasticity following auditory training in children with learning problems. Clinical
Neurophysiology, 114, 673-684. Children with learning problems exhibited
plasticity of neural encoding following participation in a remediation auditory
processing program. The plasticity was accompanied by changes in behavioral


This study suggests that children exhibit differential processing of multisensory
compared to unisensory stimuli, as has previously been reported in adults.
Multisensory integration in children: A preliminary ERP study Barbara A. Brett-
Greena,b,, Lucy J. Millera,b,c,d, William J. Gavine, Patricia L. Daviese,
dDoctoral Program in Pediatrics, Rocky Mountain University of Health
Professionals, Provo, Utah, USA eDepartment of Occupational Therapy,
Colorado State University, Fort Collins, CO, USA


J Neurophysiol 97: 3193–3205, 2007. doi:10.1152/jn.00018.2007. Multisensory
Versus Unisensory Integration: Contrasting Modes in the Superior Colliculus
Juan Carlos Alvarado, J. William Vaughan, Terrence R. Stanford, and Barry E.
Stein Department of Neurobiology and Anatomy, Wake Forest University School
of Medicine, Winston-Salem, North Carolina Multisensory versus unisensory
integration: contrasting modes in the superior colliculus. The present study
suggests that the neural computations used to integrate information from
different senses are distinct from those used to integrate information from within
the same sense. It was found that multisensory integration of cross-modal
stimulus combinations yielded responses that were significantly greater than
those evoked by the best component stimulus. In contrast, unisensory integration
of within-modal stimulus pairs yielded re- sponses that were similar to or less
than those evoked by the best component stimulus. This difference is exemplified
by the disproportionate representations of superadditive responses during
multisensory integration and the predominance of subadditive responses during
unisensory integration. These observations suggest that different rules have
evolved for integrating sensory information, one (unisensory) reflecting the
inherent characteristics of the individual sense and, the other (multisensory),
unique supramodal characteristics designed to enhance the salience of the
initiating event.
Children ages 6–12 with autism spectrum disorders (ASD) were randomly
assigned to a fine motor or SI treatment group. Pretests and posttests measured
social responsiveness, sensory processing, functional motor skills, and social–
emotional factors. Results identified significant more significant positive changes
in Goal Attainment Scaling scores and a significant decrease in autistic
mannerisms occurred in the SI group.
Pfeiffer, B. A., Koenig, K., Kinnealey, M., Sheppard, M., & Henderson, L. (2011).
Research Scholars Initiative— Effectiveness of sensory integration interventions
in children with autism spectrum disorders: A pilot study. American Journal of
Occupational Therapy, 65, 76–85. doi: 10.5014/ajot.2011.09205


The results indicate that self-stimulating behaviors were significantly reduced by
11% one hour after SI intervention. Daily ratings of self- stimulating behavior
frequency by classroom teachers using a 5-point scale correlated significantly
with the frequency counts taken by the investigators (r = 0.32, p < 0.001). These
results suggest that the sensory integration approach is effective in reducing selfstimulating
behaviors, which interfere with the ability to participate in more
functional activities. Smith, S. A., Press, B., Koenig, K. P., & Kinnealey, M.
(2005). Effects of sensory integration intervention on self-stimulating and selfinjurious
behaviors. American Journal of Occupational Therapy, 59, 418–425.


The finding that the audio tactile portion of the brain is activated as the hands
interact with the environment is of clinical significance. Vibrotactile and tactile
pressure stimuli co-activate the posterior auditory belt of the left side of the brain.
Each type of tactile input, vibrotactile-auditory and pressure tactile-auditory,
activate the posterior auditory belt. Audio tactile events occur in the brain with
vibration and pressure tactile stimuli. The finding that the audio tactile portion of
the brain is activated as the hands interact with the environment is of clinical
significance. Schurmann M, Caetano G, Hlushchuk Y, Jousmaki V, Hari R.
Touch activates human auditory cortex. NeuroImage. 2006; 30:1325-1331.1


Foxe J, Wylie G, Martinez A, et al. Auditory-somatosensory multisensory
processing in auditory cortex: an fMRI study. J Neurophysiol. 2002;88:540-543.6
Foxe and associates’ article introduces and provides support for the premise that
multisensory integration within cortical centers occurs early. Furthermore, early
integration is not initiated through unisensory centers. This study, using fMRI,
investigated the overlap of auditory and somatosensory information in the
auditory cortex of humans. Study participants were exposed to three stimuli,
auditory, tactile, and auditory and tactile combined. Auditory stimulation activated
the bilateral superior temporal gyri, which includes the primary auditory cortex,
belt, and parabelt areas. The somatosensory stimulation activated the left preand
post-central gyrus, bilateral insulae. These areas represent the primary and
secondary somatosensory cortex. Overlap between the auditory and tactile
stimulation was demonstrated in the right and left regions of the auditory cortex.
When auditory and tactile stimulation were simultaneously applied, the activation
was greater in the region of overlap in the auditory cortex. Resultant from this
study, the authors hypothesize that auditory and tactile integration provides a
feedforward process within the auditory cortex of human beings.


Murray M, Molholm S, Michael C, et al. Three principles pertaining to animal
sensory-perceptual courses. The first is the “spatial rule”. This rule states
“multisensory interactions are dependent on the spatial alignment and/or overlap
of receptive fields responsive to the stimuli.” The second rule, “temporal rule”,
maintains “that multisensory interactions are also dependent on the coincidence
of the neural responses to different stimuli.” The “inverse effectiveness rule”
reports “that the strongest stimuli, when presented in isolation, are minimally
effective in eliciting a neural response.” Grabbing your ears: rapid auditorysomatosensory
multisensory interactions in low-level sensory cortices are not
constrained by stimulus alignment. Cereb Cor. 2005;15:963-974.8 Each subject
was exposed to the following stimulations: 1) somatosensory alone, 2) auditory
alone, 3) auditory and somatosensory presented simultaneously to same location
such as left hand and ear (spatial aligned), 4) auditory and somatosensory
offered to different locations, such as left hand and right ear (spatially
misaligned). Responses to the combination auditory and somatosensory stimuli
were observed in the auditory regions of the superior temporal plane in the
hemisphere contralateral to the hand stimulated. Multisensory responses were
compared to the summed unisensory responses. The multisensory stimuli
responses, both for aligned and misaligned, were larger in amplitude than for the
summed unisensory responses. Multisensory stimulation reaction was greater
than unisensory reaction, for both spatial aligned and misaligned arrangements.
Spatially aligned and misaligned stimulation follow similar early sensory courses.
Findings suggest early auditory somatosensory inter-relationships across space
occur before perceptual-cognitive events.


Multisensory Versus Unisensory Integration: Contrasting Modes in the Superior
Alvarado JC, Vaughn JW, Stanford TR, Stein BE. Multisensory versus
unisensory integration: contrasting modes in the superior colliculus. J
Neurophysiol 97: 3193–3205, 2007. First published February 28, 2007;
doi:10.1152/jn.00018.2007. The present study suggests that the neural
computations used to integrate information from different senses are distinct from
those used to integrate information from within the same sense. Using superior
colliculus neurons as a model, it was found that multisensory integration of crossmodal
stimulus combinations yielded responses that were significantly greater
than those evoked by the best component stimulus. In contrast, unisensory
integration of within-modal stimulus pairs yielded responses that were similar to
or less than those evoked by the best component stimulus. This difference is
exemplified by the disproportionate representations of superadditive responses
during multisensory integration and the predominance of subadditive responses
during unisensory integration. These observations suggest that different rules
have evolved for integrating sensory information, one (unisensory) reflecting the
inherent characteristics of the individual sense and, the other (multisensory),
unique supramodal characteristics designed to enhance the salience of the
initiating event.


Synthesis of Information Concerning Somatosensory and Auditory Multisensory
Stimulation and Integration
Human beings in their interaction with the world do not perceive sensory events
as singular events. Sound, touch, sight, taste, smell, proprioception, and
vestibular information interact to form the processes and mechanics by which
humans learn and experience. Integration of sensory information provides a
foundation on which behavior and cognition develop and mature. Centers
previously believed to be unisensory are in fact multisensory. Schurmann M,
Caetano G, Hlushchuk Y, Jousmaki V, Hari R. Touch activates human auditory
cortex. NeuroImage. 2006;30:1325-1331.


While primary auditory and somatosensory centers in the brain exist, areas of
their sensory overlap are well documented. The location of the primary auditory
cortex and belt is in the superior temporal gyri.
1. Ozcan M, Baumgartner U, Vucurevic G, Stoeter P, Treede R. Spatial
resolution of fMRI in the human parasylvian cortex: Comparison of
somatosensory and auditory activation. NeuroImage. 2005;25(3):877- 887.
2. Kayser C, Petkov C, Augath M, Logothetis N. Integration of touch and sound in
the auditory cortex. Neuron. 2005;48:373-384.
3. Levanen S, Jousmaki V, Hari R. Vibration-induced auditory-cortex
activation in a congenitally deaf adult. Curr Biol. 1998;8:869-872.


Auditory information in conjunction with tactile input assists with making tactile
decisions. Jousmaki V, Hari R. Parchment-skin illusion: sound-biased touch. Curr
Biol. 1998;8(6):R190.


Early cortical centers are no longer thought to be unisensory. Findings of
multisensory stimulation research provide solid footing for clinical sensory
practices. When combined with theories of neural plasticity, sensory and
multisensory experiences may assist with neural development or rehabilitation.
For instance, tactile information provides stimulation of the auditory cortices in
individuals with hearing impairments; multisensory stimulation results in greater
activation of cortical centers; and sound permits individuals to make tactile
decisions. The integration of somatosensory and auditory stimulation activates
the auditory cortex of the brain. This multisensory stimulation affords more
intense cortical activation than unisensory stimulation. Somatosensory and
auditory integration is a feed forward process, not dependent on higher centers,
and occurs early in the auditory center. Tactile and auditory stimulation
simultaneously and individually may positively impact neuroplastic changes in
individuals with neurological deficits or impairments. Foxe J, Wylie G, Martinez A,
et al. Auditory-somatosensory
multisensory processing in auditory cortex: an fMRI study. J Neurophysiol.


Sensory Integration by Dana Nicholls OTR/L and Peggy Syvertson M.A. Johns
Hopkins School of Education
“Learning and paying attention is dependent upon the ability to integrate and
organize information from our senses. Everyone knows the five basic senses;
seeing, hearing, taste, smell and touch. But there are other senses that are not
as familiar including the sense of movement (vestibular), and sense of muscle
awareness (proprioception). Unorganized sensory input creates a traffic jam in
our brain making it difficult to pay attention and learn. To be successful learners,
our senses must work together in an organized manner. This is known as
sensory integration. The foundation for sensory integration is the organization of
tactile, proprioceptive and vestibular input. A person diagnosed with ADD or
ADHD, due to their difficulty paying attention, may in fact have an immature
nervous system causing sensory integration dysfunction. This makes it difficult
for him/her to filter out nonessential information, background noises or visual
distraction and focus on what is essential. The relationship between sensory
integration, learning and attention will be discussed below.
Tactile sense is our ability to learn from our environment through our sense of
touch. This includes knowing how heavy, smooth, rough, big or small an object is
just by holding it. In addition, this sense has a protective component which
causes us to pull our hand away from a hot stove. Tactile integration is important
for the development of body awareness, fine motor skills, motor planning and
being comfortable with touch. Examples of unorganized processing of tactile
input may be seen as someone who has trouble in crowds, pulls away from hugs,
is bothered by certain clothes or foods, or has to touch everything. If someone is
attending to the tags in their clothes or the seams in their socks, they are not able
to focus on what you are saying; they are not ready to learn.
Vestibular sense provides information related to movement and head position.
The vestibular sense is important for development of balance, coordination, eye
control, attention, being secure with movement, emotional security and some
aspects of language development. Disorganized processing of vestibular input
may be seen when someone has difficulty with attention, coordination, following
directions, reading (keeping eyes focused on the page or board) or eye-hand
coordination. Disorganization may also be seen in someone who is constantly in
motion, has an extreme fear of movement, or is described as an overly sensitive,
lazy or sedentary person. Immature language skills can often be the reason a
child is initially referred for therapy, but the language delay may be the result of
immature sensory processing.
Proprioception is our ability to know where our muscles and joints are in space
and how they are moving. This is very important for the development of body
awareness. Our proprioceptive sense cannot work in isolation, but requires
constant input from our tactile and vestibular systems. Unorganized processing
of proprioceptive input may be seen as someone who is clumsy, falls or stumbles
frequently, is overly aggressive (e.g., tackles people), walks on toes, constantly
chewing on food or objects, has difficulty motor planning, or is messy at
mealtime. Someone who is unconsciously worried about where their body is on
the chair or how they will walk around the table without bumping into it, will not be
able to focus their attention on what is being said or what they are carrying.
When the above sensory systems are intact, learning is effortless and easy.
Immature systems make paying attention and therefore learning difficult and
About the AuthorsDana Nicholls, OTR/L, is an Occupational Therapist in
Washington State. She is a Certified Sensory Integration Therapist, who was
trained at The Ayres Clinic. She is currently in private practice serving clients in
the greater Puget Sound area. Dana can be reached via email at or fax at 253-853-4308.
Peggy Syvertson CCC-SLP, is a Speech and Language Pathologist in
Washington State. She has her Master's and an Interdisciplinary Certificate as an
Early Intervention Specialist. She is currently working in private practice and
within the schools in the greater Puget Sound area. Peggy can be reached via
email at


Vestibular and visual stimulation together, especially the vestibular
part, may benefit children with ADHD
Arnold, L. E., Clark, D. L., Sachs, L. A., Jakim, S., & Smithies, C. (1985).
Vestibular and visual rotational stimulation as treatment for attention deficit and
hyperactivity. American Journal of Occupational Therapy, 39, 84–91.


Motor learning relies on integrated sensory inputs in ADHD, but over-selectively
on proprioception in autism spectrum conditions. Slower rate of adaptation and
anomalous bias towards proprioceptive feedback during motor learning are
characteristics of autism, whereas increased variability in execution is a
characteristic of ADHD. Autism Res. 2012 Apr;5(2):124-36. doi:
10.1002/aur.1222. Epub 2012 Feb 22. Izawa J, Pekny SE, Marko MK, Haswell
CC, Shadmehr R, Mostofsky SH.


Sensory Modulation Dysfunction in Children with ADHD, Mangeot, et al,
Colorado health Science Center; Summary: Children with ADHD symptoms
displayed greater abnormalities in sensory modulation.


Eric Courchesne, Ph.D., of the Neurosciences Department, University of
California at San Diego, has found significant impairments in auditory processing
in autistic individuals using P300 brain wave technology (see Courchesne, 1987
for a review). The P300 brain wave occurs 300 milliseconds after the
presentation of a stimulus. (The ‘P’ refers to the positive polarity of the brain
wave.) The P300 is associated with cognitive processing, and this brain wave is
considered an indication of long-term memory retrieval (Donchin, Ritter, &
McCallum, 1978). Edelson et al. (1999) examined auditory P300 activity prior to
and three months following auditory integration training (AIT). Three subjects with
autism participated in the experimental AIT group and two others participated in a
placebo group. Prior to AIT, all five individuals had abnormal auditory P300
activity, indicating problems. Three months following AIT, the results showed
dramatic improvement in P300 activity for those who received AIT (i.e., a
normalization of P300 activity) and found no change in those who received the
Atypical sensory-based behaviors are a ubiquitous feature of autism spectrum
disorders (ASDs). In this article, we review the neural underpinnings of sensory
processing in autism by reviewing the literature on neurophysiological responses
to auditory, tactile, and visual stimuli in autistic individuals. We review studies of
unimodal sensory processing and multisensory integration that use a variety of
neuroimaging techniques, including electroencephalography (EEG),
magnetoencephalography (MEG), and functional MRI. We then explore the
impact of covert and overt attention on sensory processing. With additional
characterization, neurophysiologic profiles of sensory processing in ASD may
serve as valuable biomarkers for diagnosis and monitoring of therapeutic
interventions for autism and reveal potential strategies and target brain regions
for therapeutic interventions. Pediatric Research (2011) 69, 48R–54R;


Sensory Processing in Autism: A Review of Neurophysiologic Findings, Elysa
J Marco1, Leighton B N Hinkley2, Susanna S Hill2 and Srikantan S Nagarajan3
Autism spectrum disorders (ASDs) are defined clinically by impairment in
communication, social interaction, and behavioral flexibility (1). There is mounting
evidence for disruption of the auditory and visual processing pathways and a
surging interest in multisensory integration (MSI). of page
There is literature suggesting measurable differences in early auditory pathways,
especially with increasingly complex stimuli. Understanding the nature of this
fundamental step in the auditory sensory stream is crucial because the ability to
acquire and parse a variety of incoming sounds forms the foundation for
language and communication.
In general, the neurophysiologic study of auditory processing in autism does
suggest atypical neural activity as early in the processing stream as the primary
auditory cortex. However, as Whitehouse and Bishop (24) suggest, these
differences may be a result of top-down inhibitory processes mediating encoding
and early sound processing. It is probable that the atypical processing is related
to the unusual behavioral responses so commonly observed in children on the
autism spectrum such as covering of the ears to seemingly benign sounds such
as the vacuum cleaner and the blender. Furthermore, one might conjecture that if
the auditory input is perceived as unpleasant or noxious, affected individuals will
learn to avoid auditory input, and thus curtail the learning that comes from
listening to the people and world around them. Comprehension of the potentially
atypical auditory processing in children with autism may be key to parsing
different etiologies of autism, targeting treatments to children with auditory
hyper/hypo-sensitivities, and ameliorating overwhelming auditory sensory input to
facilitate learning.ctile Sensory Processing
Although tactile sensitivity is commonly reported in ASD, it has received far less
attention in the neuroscience literature than auditory sensitivity (25). Common
clinical complaints are avoiding light touch to the head and body as occur with
grooming and particular clothing. The psychophysical tactile studies look at
thresholds and sensitivity using vibrotactile stimuli. Adults with AS showed lower
tactile perceptual thresholds for 200 Hz but not 30 Hz vibrotactile stimuli, implying
a specific hypersensitivity in the Pacinian corpuscles receptor pathway (3).
Tactile hypersensitivity was again shown to vibrotactile stimuli as well as thermal
stimuli but not to light touch in adults with autism (26). In contrast, in a small
sample of children with autism, there were no tactile perceptual threshold
differences for vibrotactile (40 and 250 Hz) detection (27). However, this study
did suggest a correlation between a measure of behavioral tactile sensitivity
phenotype and emotional/social reaction. (This trend is considerably
underpowered with a sample size of only six boys.) Beyond threshold
investigation, Miyazaki et al. (28) demonstrate an enhanced early (low-level)
somatosensory evoked potential peak in young autistic children using median
nerve stimulation that was most prevalent in the right hemisphere response.
Coskun et al. (29) most recently investigated somatosensory mapping in high
functioning adults with autism using MEG. High functioning adults with autism
appear to have a disrupted cortical representation of their face and hand. Again,
because of the heterogeneity of ASD, the electrophysiology and functional
imaging work in this domain should include behavioral measures so that within
group differences do not obscure real between group differences. There is a
tremendous need for further exploration in this domain as atypical tactile
sensitivity appears with particularly high frequency in the autism population.of
Individuals with ASD also exhibit atypical visual behavior that can be construed
as attempting to avoid visual input (e.g. covering eyes at bright lights) or to seek
additional visual stimuli (e.g. twisting fingers in front of eyes) (4). Similar to the
auditory and tactile domains, there is considerable discrepancy in
neurophysiological findings. There are suggestive reports in the visual domain of
enhanced detail perception, particularly for simple stimuli with impairment in
more complex tasks (30). Some visual-evoked potential studies indicate that
individuals with ASD possess atypical early peaks with impairments in object
boundary detection (33), decreased contrast detection ability in both still and
moving stimuli at a range of signal/noise ratios (34), and undifferentiated
responses for mid- and high spatial frequency gratings (35). Local motion
processing studies show differences in second order (texture defined) motion
processing but intact first-order (luminance defined) processing, suggesting
difficulties with effective integration of incoming stimuli that is magnified with
more nuanced tasks (36).
One of the most well-studied aspects of visual perception in autism is that of face
processing given the pertinence of this skill for human social interaction (37). As
Klin (38) suggests, the literature is heavily confounded by differences in the
familiarity of the face, attention, gaze direction and fixation, and the
type/complexity of the stimulus. A functional MRI study with eye tracking shows
that activation of the fusiform gyrus and the amygdala is reduced in an ASD
cohort, as well as their unaffected siblings, but correlates positively with fixation
time on the eye region of the face (39,40). An ERP study again highlights group
differences that are dependent on directed attention such that ASD individuals do
not show the expected increase in the N170 (face processing) wave with directed
attention (41). An EEG study assessing γ-band activity, thought to represent the
binding of visual information, gives convergent evidence for a neurophysiologic
difference in AS face processing (42). Furthermore, the type of visual information
matters; children with autism may respond more robustly than controls to neutral
and detailed, high spatial frequency information and less robustly to the rapid
low-frequency processing that is so critical to our fast-paced social world (43).
The emotional valence of face processing has been investigated with a recent
study suggesting hyperactivity in the right amygdala with altered connectivity
between the frontal and temporal lobes (44). It is a challenge to interpret whether
these differences represent primary cortical abnormalities, result from decreased
visual exploration in early infancy, or are secondary to a primary social cognitive
Deficits in simple stimuli and faces extend to studies of biological motion, such
that children with autism show impairments in the processing of dynamic noise,
motion coherence, and form-from-motion detection (45). There are suggestions
that this observed deficit may result in part from atypical processing of emotional
information as children with autism were found to differ from control children only
in their ability to name emotional point-light displays and not point-light displays
of everyday objects (46). This finding suggests a potential disconnection from the
limbic or “emotion” neural networks that inform primary sensory processing.
Speaking to a genetic underpinning for these differences, inefficient motion
processing has been found in siblings of individuals with ASD as well (47). In
accordance with theories of increased local cortical activity (48) with impaired
long-range connectivity (49), individuals with autism appear to be over-recruiting
their left primary cortex compared with typicals during a motion coherence
functional MRI study (50). Taken as a whole, these studies further support a
disruption in the processing of basic unimodal sensory information that forms the
backbone of higher order cortical abilities such as socialization.Low-Level
Multisensory Integration
Similar to the aforementioned deficits in unimodal sensory processing in children
with ASD, these individuals may also perform poorly during conditions that
require collapsing information across multiple modalities (or MSI). Many of the
atypical perceptual experiences reported in those with ASD are believed to be
due to an inability to properly filter or process simultaneous channels of visual,
auditory, and tactile inputs (51). There is evidence that sensory illusions that
require the proper concatenation of inputs across multiple domains operate at a
different level in ASD, compared with typically developing individuals. In the
“flash-beep” illusion, multiple auditory tones paired with a single transient visual
stimuli can induce the perception that multiple flashes are present. At a cursory
level, it appears that the integration necessary to produce this illusion is
preserved in ASD, as demonstrated through a lack of difference between
patients and Intelligence Quotient (IQ)-matched typical individuals (52). However,
when the timing between stimulus sets is perturbed during presentation, deficits
in processing begin to emerge in subjects with autism. Typically, disparity
between the auditory and visual stimulus onset times will impact the effect of the
illusion, until they appear uncoupled at a certain threshold. Foss-Feig et al. (53)
were able to demonstrate that, in subjects with autism, the time duration between
stimuli that continue to produce the illusion are broader than in typically
developing individuals. The observation that broader temporal gaps continue to
produce a “flash-beep” illusion in individuals with ASD suggests a level of
inefficiency in the MSI in this population.
Electrophysiological studies probe the neural mechanisms of ASD that can
manifest as behavioral multisensory deficits. EEG studies of multisensory
processing have reported abnormal timing and level of activity within
electrophysiological signatures of brain processing. Courchesne et al. (54,55)
report that in individuals with ASD, a reduction in response amplitude (compared
with typically developing children) is evident when concurrent auditory and visual
stimuli streams are presented. The sequence of activity in the brain during MSI
seems to deviate in children with autism, particularly within the later stages of
processing when sensory information is collapsed. When auditory and
somatosensory stimuli are presented in parallel, early (<100 ms) electrical
potentials in primary sensory cortices are relatively spared in ASD; however,
responses that follow this initial stage of activity in the cortex (at around 175 ms)
are limited and delayed in ASD (56). These investigations indicate that both the
magnitude and the latency of activity in the brain may contribute to multisensory
processing deficits in ASD.
Although both behavioral and neurophysiological processing impairments in
simple MSI have been reported in ASD, salient differences in sensory integration
are also evident at a complex level, particularly during speech comprehension
and production. When audio and visual speech stimuli are staggered and
presented to individuals with autism, performance drops to a chance level and
indicates deficits in speech comprehension (57). Multimodal illusions of linguistic
processing in ASD, such as the McGurk effect, suggest that improper timing of
sensory integration contributes to observable deficits in communication in ASD.
In the McGurk effect, visual processing (e.g. lip reading) is combined with
auditory processing (phoneme perception) to produce the comprehension of
spoken language. Although both typically developing and ASD individuals
perform well during this task, typical individuals show a greater dependence on
visual feedback (lip reading) compared with ASD (58,59). When both groups are
trained on the visual feedback component of the McGurk effect, ASD participants
fail to show improvements in performance (60,61). Furthermore, a reliance on
visual feedback in noisy auditory environments is unattainable for ASD
participants (61). An inability to “fall back” on certain sets of sensory stimuli in the
presence of challenging environmental stimuli may contribute to the
communication deficits that are well characterized in this disorder.
MSI investigations exploring the specific neurophysiological mechanisms that are
compromised in ASD is just beginning (62). Many of the regions known to
integrate multiple sensory inputs have been implicated, including prefrontal
cortex and association regions of the temporal lobe. At the cellular level,
postmortem studies of ASD have illustrated that the columnar density in the
neocortex is dense in autism, potentially facilitating local processing (63). It has
also been hypothesized that the cerebellum, a structure that shows significant
changes in neuronal density in autism (64), may play a role in impaired sensory
integration in the disorder. This mediation could occur through atypical filtering of
afferent inputs, although these exact mechanisms are unclear (65). Many of the
neocortical fields that play a role in MSI are also part of a putative “mirror neuron”
network, first identified in homologues of these regions in nonhuman primates
(66). Given the observable deficits in imitation and empathy known to be a core
feature of the autism spectrum, it has been proposed that communication deficits
arise from an inability of multisensory “mirror neurons” to concatenate information
to facilitate higher order cognitive function (67). However, others propose that as
sensory integration is dependent on the rapid exchange of information between
distinct cortical and subcortical regions, disruptions in connectivity likely play the
causative role (68). The ASD literature suggests both direct axonal disconnection
such as has been implied by the abnormalities of the corpus callosum (69) and
indirect disruption of long-range firing synchrony (70,71).
The discussion of sensory processing in ASD would be incomplete without the
consideration of the role of attention on cognitive processing. In their review,
Allen and Courchesne (72) suggest that that the clinical observation of
heightened reactivity to seemingly meaningless stimuli (e.g. intense tantrums in
response to the hum of a blender) may be related to a neurobehavioral driven
distractibility. Furthermore, narrowed interest and repetitive behaviors may
represent deficits in attentional shifting. However, even defining attention is a
challenging matter. According to Talsma et al. (73), “attention is a relatively broad
cognitive concept that includes a set of mechanisms that determine how
particular sensory input, perceptual objects, trains of thought, or courses of
action are selected for further processing from an array of concurrent possible
stimuli, objects, thoughts and actions.” Functionally, an individual must be able to
select certain sensory inputs for enhanced processing while either filtering out or
suppressing others. This selective attention can be further subdivided in
operations such as attentional switching and sustained attention over time (74–
76). Many brain regions are involved in processing, modulating, and integrating
sensory information. There has been a particular focus on the superior colliculus,
the cerebellum, and the frontal lobes in understanding this rapid and
multidirectional flow of information, which is mediated by attentional demands
and resources (77,78). We suggest that this multidirectional flow of information is
impaired for individuals with ASD and that this disruption in cortical
communication underlies the individual's inability to attend to their environment in
a flexible, productive, and meaningful way. In the following sections, we will focus
on two aspects of attending: first, the ability to shift focus from stimuli of one type
to another (attentional switching); and second, the effect of increasing the array
of information presented to measure the subject's ability to select what
information needs to be attended to and what needs to be ignored (selective
In this section, we will focus on studies in which the subject shifts their attention
to changes in the stimuli. In ASD neurophysiologic research, the most common
form of attentional switch is between a repeated stimulus and an unfamiliar or
novel stimulus within the same sensory modality (exogenous attention).
However, shifting paradigms can also require the subject to move from one
modality to another or to shift visual or auditory focus in space (endogenous
attention). In the auditory domain, researchers have primarily used the oddball
paradigm to investigate attentional shift. In the oddball paradigm, a stimulus that
varies on a single parameter (deviant) such as duration, frequency or intensity, is
randomly inserted into a train of repeated (standard) stimuli. This deviance leads
to the generation of a negative deflection on an evoked potential recording at
150–200 ms, which is best recorded from the fronto-central sites (79). This
paradigm can be extended from covert (preattentive) to overt attention with a
task requiring a response to the deviant (target), and other variations of this
paradigm include a third rare stimuli as a nontarget (novel) comparison. In the
oddball paradigm, the difference between the neural response to the standard
stimuli and the deviant stimuli is called the mismatch negativity (MMN) when
using an EEG recording technique or the mismatch field when using MEG.
MMN/mismatch field wave forms have generated widely disparate results from
normal in an ERP study of high functioning children with autism (80) to
completely absent in an MEG study of low-functioning individuals with autism
(81). Although there are conflicting data from other studies (82–85), Gomot et al.
(86,87) report faster MMN latencies for pitch variation and atypical activation of
the left anterior cingulate. This location has been implicated in attentional
switching and correlated with a behavioral measure of intolerance to change.
This reduced mismatch latency to pitch variation in conjunction with superior
pitch recognition has been interpreted to support the theory of perceptual
enhancement, whereby local processing networks are over connected at the
expense of long-range connections with integration and attention networks (88–
Conflicting findings have also been reported for auditory MMN amplitudes.
Several groups have found increased MMN amplitude in samples of adults and
children with AS and ASD (19,91,92), whereas Dunn et al. (12) found reduced
MMN amplitudes using a passive paradigm. Attention shifting for individuals with
autism has received less focus in the visual and somatosensory domains,
perhaps related to the intense interest in the auditory domain as the gateway for
understanding the language and communication deficits that are central to ASDs.
When Kemner et al. (93) assessed the role of visual attention using an oddball
paradigm with both a passive condition and an active counting task, they found
that children with autism did not differ from controls in the passive condition, but
they did show a larger response to the deviant stimuli during the active task
The importance of directed or overt attention on the effects of cortical processing
of novelty is further highlighted by the work of Whitehouse and Bishop (24). To
clarify previous findings, suggesting that orienting deficits in autism might be
speech-sound specific (80), Whitehouse and Bishop performed a layered study
of boys with high functioning autism examining whether processing deficits were
due to a perceptual impairment (in acoustic encoding or discrimination of
different speech sounds) or a function of cognitive factors (such as reduced
attention). They found that, during a passive condition, children with autism
showed attenuated early cortical responses to speech sounds but not complex
tones. However, when the children were instructed to attend to and respond to
the deviant condition, these amplitude differences were no longer evident.
Similarly, Dunn et al. (12) found that the decreased MMN to simple stimuli,
apparent during a passive condition, normalized with directed attention. These
studies suggest that a “top down” process mediated by directed attention
influences basic sensory processing for individuals on the autism spectrum.age
Beyond the effects of attentional shifting, there is interest in how individuals with
ASD select what information to attend to, what to ignore, and how this guides
their ability to make sense of the changing world around them. In EEG/MEG
studies of attentional shift, one response property of interest is the P300. The
P3a is a positive deflection culminating around 300 ms that is thought to reflect
orienting to changes in the environment that may underlie attentional switching;
the P3b is a component of the late attention peak that reflects task-related
cortical activity and may underlie working memory. The P3b is thought to
emanate from temporal and parietal neural sources (94). The earliest autism
study reporting a P300 attention wave targeted attention by presenting a train of
stroboscopic flashes with an occasional missing flashes (95). In the three
individuals investigated, the study investigators found good accuracy in the
behavioral task but small or absent late positive waves. This suggests, as has
been seen in the auditory literature, that in simple tasks, behavioral performance
can be similar between groups while the cortical activity differs. In a series of
visual oddball studies, Courchesne et al. (54) first used a letter mismatch and
found normal P3b amplitudes; in a later study, they used blue and red squares
(color mismatch) and again found typical P3b responses with targeted attention
(54,55). In a subsequent study, they added an additional level of spatial
complexity to the task—there were five empty squares, one of which was
designated to be attended to; when the circle appeared in the attended box
(target), the participant responded with a button press; when the circle appeared
in an “un”attended box, the condition was ignored. In this visual-spatial selective
attention task, they found a delay in the frontal P3a (attention orienting) and a
diminution in the parietal P3b (96). With this degree of spatial challenge, this
cohort of high functioning ASD males had difficulty in both speed and accuracy
relative to matched controls. This series suggests that increasing the attention
and capacity demands of this visual task leads to both behavioral and physiologic
differences in individuals with autism versus controls, whereas simple visual
attention tasks may fail distinguish them. Other visual oddball studies support this
finding of diminished P3 amplitudes and have correlated a shorter visual fixation
period with the P3 diminution (93,97). These investigations suggest that the
density and complexity of the incoming stimuli may affect the degree to which the
attention neural networks are recruited for processing of incoming sensory
Our ability to attend appears to have a limited capacity (i.e. there is a finite
quantity of information that can be considered simultaneously), and we therefore
need to selectively concentrate on one aspect of the environment while ignoring
other features to effectively and efficiency process sensory input (75). This
capacity may be even more limited in certain subgroups of individuals with ASD.
An ERP auditory task with selected spatial attention demonstrates this capacity
effect: high functioning adults with autism showed both behaviorally diminished
ability to selectively tune into a specified sound source as well as an ERP
signature of this deficit with relatively broader N1 and shallower P3 peaks when
compared with a typical control group (98). This finding was only evident with
increased task complexity (i.e. more speakers and a continuous, rapid stream of
complex tone distractors). In a task of divided attention between visual and
auditory stimuli, the failure of the autism group to modulate the slow negative
wave in response to focused/divided/ignored conditions is thought to indicate a
potential deficit in selective inhibition and attention (99). This finding echoes the
anecdotal reports of parents that children with autism can function typically in a
well-controlled environment but decompensate in the face of challenging sensory
environments such as a grocery store or an animated birthday party. Children
with autism may have more difficulty with automatic processing of information
and may already rely more heavily on already overloaded attention and workingmemory
based networks, such that when the stimuli reach and exceed capacity,
the processing system fails (12,90).
Given the ubiquitous nature of sensory behavioral differences for individuals with
autism, understanding the neural underpinnings of basic sensory processing in
ASDs is an important task. Furthermore, as the neurophysiologic data mount, we
suggest that differences in sensory processing may actually cause core features
of autism such as language delay (auditory processing) and difficulty with reading
emotion from faces (visual processing). Interpreting the neuroscience has been
complicated by the heterogeneity of the disorder as well as the difficulty in
designing tasks that can precisely probe our finely tuned and intricately
connected sensory neural networks. Despite these challenges, tremendous gains
have been made over the past 30 years and will guide both our understanding of
the disorder as well as provide insights into how to strengthen basic processing
and attention for affected individuals.
Going forward, studies of infant siblings of individuals affected with ASD can
provide an understanding of whether sensory processing differences are a
primary feature of the disorder or a result of learned behaviors. Behavioral
intervention trials, such as computerized training modules and self-regulation
programs, need to be studied both for efficacy and to determine whether there is
normalization of neural activity in affected individuals. Psychopharmacology
studies targeting attention and arousal paired with functional imaging
assessments hold great promise in providing valuable treatment models. Finally,
careful sensory behavioral phenotyping is essential for both understanding our
neurophysiologic research as well as tailoring appropriate and effective
• American Psychiatric Association1994 Diagnostic and Statistical Manual of
Mental Disorders: DSM-IV. 4th ed. American Psychiatric Association,
Washington, D.C
• Minshew NJ, Sweeney J, Luna B 2002 Autism as a selective disorder of
complex information processing and underdevelopment of neocortical
systems. Mol Psychiatry 7:S14–S15 | Article |
• Blakemore SJ, Tavassoli T, Calo S, Thomas RM, Catmur C, Frith U, Haggard
P 2006 Tactile sensitivity in Asperger syndrome. Brain Cogn 61:5–13
• Leekam SR, Nieto C, Libby SJ, Wing L, Gould J 2007 Describing the sensory
abnormalities of children and adults with autism. J Autism Dev Disord
37:894–910 | Article | PubMed | ISI |
• Tomchek SD, Dunn W 2007 Sensory processing in children with and without
autism: a comparative study using the short sensory profile. Am J Occup
Ther 61:190–200
• Crane L, Goddard L, Pring L 2009 Sensory processing in adults with autism
spectrum disorders. Autism 13:215–228
• Asperger H 1944 [Autistic psychopathy in childhood]. Arch Psychiatr Nervenkr
117:76–136 | Article |
• Kanner L 1943 Autistic disturbances of affective contact. Nervous Child 2:217–
250 | ISI |
• Grandin T 1995 Thinking in Pictures; and other reports from my life with
autism. Doubleday, New York
• Baranek GT, David FJ, Poe MD, Stone WL, Watson LR 2006 Sensory
Experiences Questionnaire: discriminating sensory features in young
children with autism, developmental delays, and typical development. J
Child Psychol Psychiatry 47:591–601
• Ben-Sasson A, Hen L, Fluss R, Cermak SA, Engel-Yeger B, Gal E 2009 A
meta-analysis of sensory modulation symptoms in individuals with autism
spectrum disorders. J Autism Dev Disord 39:1–11
• Ayres AJ, Tickle LS 1980 Hyper-responsivity to touch and vestibular stimuli as
a predictor of positive response to sensory integration procedures by
autistic children. Am J Occup Ther 34:375–381 | PubMed |
• Baranek GT, Foster LG, Berkson G 1997 Tactile defensiveness and
stereotyped behaviors. Am J Occup Ther 51:91–95
• Dunn MA, Gomes H, Gravel J 2008 Mismatch negativity in children with autism
and typical development. J Autism Dev Disord 38:52–71
• Courchesne E, Courchesne RY, Hicks G, Lincoln AJ 1985 Functioning of the
brain-stem auditory pathway in non-retarded autistic individuals.
Electroencephalogr Clin Neurophysiol 61:491–501
• Rosenhall U, Nordin V, Brantberg K, Gillberg C 2003 Autism and auditory brain
stem responses. Ear Hear 24:206–214
• Kwon S, Kim J, Choe BH, Ko C, Park S 2007 Electrophysiologic assessment of
central auditory processing by auditory brainstem responses in children
with autism spectrum disorders. J Korean Med Sci 22:656–659
• Källstrand J, Olsson O, Nehlstedt SF, Sköld ML, Nielzén S 2010 Abnormal
auditory forward masking pattern in the brainstem response of individuals
with Asperger syndrome. Neuropsychiatr Dis Treat 6:289–296
• Russo N, Nicol T, Trommer B, Zecker S, Kraus N 2009 Brainstem transcription
of speech is disrupted in children with autism spectrum disorders. Dev Sci
• Russo NM, Skoe E, Trommer B, Nicol T, Zecker S, Bradlow A, Kraus N 2008
Deficient brainstem encoding of pitch in children with Autism Spectrum
Disorders. Clin Neurophysiol 119:1720–
1731 | Article | PubMed | ChemPort |
• Ferri R, Elia M, Agarwal N, Lanuzza B, Musumeci SA, Pennisi G 2003 The
mismatch negativity and the P3a components of the auditory event-related
potentials in autistic low-functioning subjects. Clin Neurophysiol
• Martineau J, Garreau B, Barthelemy C, Lelord G 1984 Evoked potentials and
P300 during sensory conditioning in autistic children. Ann N Y Acad Sci
• Bruneau N, Bonnet-Brilhault F, Gomot M, Adrien JL, Barthelemy C 2003
Cortical auditory processing and communication in children with autism:
electrophysiological/behavioral relations. Int J Psychophysiol 51:17–25
• Oram Cardy JE, Flagg EJ, Roberts W, Roberts TP 2008 Auditory evoked fields
predict language ability and impairment in children. Int J Psychophysiol
• Roberts TP, Khan SY, Rey M, Monroe JF, Cannon K, Blaskey L, Woldoff S,
Qasmieh S, Gandal M, Schmidt GL, Zarnow DM, Levy SE, Edgar JC 2010
MEG detection of delayed auditory evoked responses in autism spectrum
disorders: towards an imaging biomarker for autism. Autism Res 3:8–18
• Whitehouse AJ, Bishop DV 2008 Do children with autism ‘switch off' to speech
sounds? An investigation using event-related potentials. Dev Sci 11:516–
• Wiggins LD, Robins DL, Bakeman R, Adamson LB 2009 Brief report: sensory
abnormalities as distinguishing symptoms of autism spectrum disorders in
young children. J Autism Dev Disord 39:1087–1091
• Cascio C, McGlone F, Folger S, Tannan V, Baranek G, Pelphrey KA, Essick G
2008 Tactile perception in adults with autism: a multidimensional
psychophysical study. J Autism Dev Disord 38:127–
137 | Article | PubMed |
• Güçlü B, Tanidir C, Mukaddes NM, Unal F 2007 Tactile sensitivity of normal
and autistic children. Somatosens Mot Res 24:21–33
• Miyazaki M, Fujii E, Saijo T, Mori K, Hashimoto T, Kagami S, Kuroda Y 2007
Short-latency somatosensory evoked potentials in infantile autism:
evidence of hyperactivity in the right primary somatosensory area. Dev
Med Child Neurol 49:13–17
• Coskun MA, Varghese L, Reddoch S, Castillo EM, Pearson DA, Loveland KA,
Papanicolaou AC, Sheth BR 2009 How somatic cortical maps differ in
autistic and typical brains. Neuroreport 20:175–
179 | Article | PubMed | ISI |
• Bertone A, Mottron L, Jelenic P, Faubert J 2005 Enhanced and diminished
visuo-spatial information processing in autism depends on stimulus
complexity. Brain 128:2430–2441 | Article |
• de Jonge MV, Kemner C, de Haan EH, Coppens JE, van den Berg TJ, van
Engeland H 2007 Visual information processing in high-functioning
individuals with autism spectrum disorders and their parents.
Neuropsychology 21:65–73
• Koh HC, Milne E, Dobkins K 2010 Spatial contrast sensitivity in adolescents
with autism spectrum disorders. J Autism Dev Disord 40:978–987
• Vandenbroucke MW, Scholte HS, van Engeland H, Lamme VA, Kemner C
2008 A neural substrate for atypical low-level visual processing in autism
spectrum disorder. Brain 131:1013–1024
• Sanchez-Marin FJ, Padilla-Medina JA 2008 A psychophysical test of the visual
pathway of children with autism. J Autism Dev Disord 38:1270–1277
• Jemel B, Mimeault D, Saint-Amour D, Hosein A, Mottron L 2010 VEP contrast
sensitivity responses reveal reduced functional segregation of mid and
high filters of visual channels in autism. J Vis 10:13
• Bertone A, Mottron L, Jelenic P, Faubert J 2003 Motion perception in autism: a
“complex” issue. J Cogn Neurosci 15:218–225 | Article | PubMed | ISI |
• Schultz RT 2005 Developmental deficits in social perception in autism: the role
of the amygdala and fusiform face area. Int J Dev Neurosci 23:125–
141 | Article | PubMed |
• Klin A 2008 Three things to remember if you are a functional magnetic
resonance imaging researcher of face processing in autism spectrum
disorders. Biol Psychiatry 64:549–551
• Dalton KM, Nacewicz BM, Johnstone T, Schaefer HS, Gernsbacher MA,
Goldsmith HH, Alexander AL, Davidson RJ 2005 Gaze fixation and the
neural circuitry of face processing in autism. Nat Neurosci 8:519–
526 | Article | PubMed | ISI | ChemPort |
• Dalton KM, Nacewicz BM, Alexander AL, Davidson RJ 2007 Gaze-fixation,
brain activation, and amygdala volume in unaffected siblings of individuals
with autism. Biol Psychiatry 61:512–520 | Article | PubMed | ISI |
• Churches O, Wheelwright S, Baron-Cohen S, Ring H 2010 The N170 is not
modulated by attention in autism spectrum conditions. Neuroreport
• Grice SJ, Spratling MW, Karmiloff-Smith A, Halit H, Csibra G, de Haan M,
Johnson MH 2001 Disordered visual processing and oscillatory brain
activity in autism and Williams syndrome. Neuroreport 12:2697–
2700 | Article | PubMed | ISI | ChemPort |
• Vlamings PH, Jonkman LM, van Daalen E, van der Gaag RJ, Kemner C 2010
Basic abnormalities in visual processing affect face processing at an early
age in autism spectrum disorder. Biol Psychiatry 68:1107–1113
• Monk CS, Weng SJ, Wiggins JL, Kurapati N, Louro HM, Carrasco M,
Maslowsky J, Risi S, Lord C 2010 Neural circuitry of emotional face
processing in autism spectrum disorders. J Psychiatry Neurosci 35:105–
• Annaz D, Remington A, Milne E, Coleman M, Campbell R, Thomas MS,
Swettenham J 2010 Development of motion processing in children with
autism. Dev Sci 13:826–838
• Parron C, Da Fonseca D, Santos A, Moore DG, Monfardini E, Deruelle C 2008
Recognition of biological motion in children with autistic spectrum
disorders. Autism 12:261–274
• Koh HC, Milne E, Dobkins K 2010 Contrast sensitivity for motion detection and
direction discrimination in adolescents with autism spectrum disorders and
their siblings. Neuropsychologia 48:4046–4056
• Rubenstein JL, Merzenich MM 2003 Model of autism: increased ratio of
excitation/inhibition in key neural systems. Genes Brain Behav 2:255–
267 | Article | PubMed | ISI | ChemPort |
• Belmonte MK, Cook EHJr, Anderson GM, Rubenstein JL, Greenough WT,
Beckel-Mitchener A, Courchesne E, Boulanger LM, Powell SB, Levitt PR,
Perry EK, Jiang YH, DeLorey TM, Tierney E 2004 Autism as a disorder of
neural information processing: directions for research and targets for
therapy. Mol Psychiatry 9:646–663 | Article | PubMed | ISI | ChemPort |
• Brieber S, Herpertz-Dahlmann B, Fink GR, Kamp-Becker I, Remschmidt H,
Konrad K 2010 Coherent motion processing in autism spectrum disorder
(ASD): an fMRI study. Neuropsychologia 48:1644–1651
• O'Neill M, Jones RS 1997 Sensory-perceptual abnormalities in autism: a case
for more research?. J Autism Dev Disord 27:283–293
• van der Smagt MJ, van Engeland H, Kemner C 2007 Brief report: can you see
what is not there? Low-level auditory-visual integration in autism spectrum
disorder. J Autism Dev Disord 37:2014–2019
• Foss-Feig JH, Kwakye LD, Cascio CJ, Burnette CP, Kadivar H, Stone WL,
Wallace MT 2010 An extended multisensory temporal binding window in
autism spectrum disorders. Exp Brain Res 203:381–
389 | Article | PubMed | ISI |
• Courchesne E, Lincoln AJ, Kilman BA, Galambos R 1985 Event-related brain
potential correlates of the processing of novel visual and auditory
information in autism. J Autism Dev Disord 15:55–76
• Courchesne E, Lincoln AJ, Yeung-Courchesne R, Elmasian R, Grillon C 1989
Pathophysiologic findings in nonretarded autism and receptive
developmental language disorder. J Autism Dev Disord 19:1–
17 | PubMed |
• Russo N, Foxe JJ, Brandwein AB, Altschuler T, Gomes H, Molholm S 2010
Multisensory processing in children with autism: high-density electrical
mapping of auditory-somatosensory integration. Autism Res 3:253–267
• Bebko JM, Weiss JA, Demark JL, Gomez P 2006 Discrimination of temporal
synchrony in intermodal events by children with autism and children with
developmental disabilities without autism. J Child Psychol Psychiatry
• Williams JH, Massaro DW, Peel NJ, Bosseler A, Suddendorf T 2004 Visualauditory
integration during speech imitation in autism. Res Dev Disabil
• de Gelder B, Vroomen J, van der Heide L 1991 Face recognition and lipreading
in autism. Eur J Cogn Psychol 3:69–86
• Smith EG, Bennetto L 2007 Audiovisual speech integration and lipreading in
autism. J Child Psychol Psychiatry 48:813–821
• Iarocci G, Rombough A, Yager J, Weeks DJ, Chua R 2010 Visual influences
on speech perception in children with autism. Autism 14:305–320
• Foxe JJ, Molholm S 2009 Ten years at the Multisensory Forum: musings on
the evolution of a field. Brain Topogr 21:149–154
• Casanova MF, Buxhoeveden DP, Brown C 2002 Clinical and macroscopic
correlates of minicolumnar pathology in autism. J Child Neurol 17:692–
• Ritvo ER, Freeman BJ, Scheibel AB, Duong T, Robinson H, Guthrie D, Ritvo A
1986 Lower Purkinje cell counts in the cerebella of four autistic subjects:
initial findings of the UCLA-NSAC Autopsy Research Report. Am J
Psychiatry 143:862–866 | PubMed | ISI | ChemPort |
• Kern JK 2002 The possible role of the cerebellum in autism/PDD: disruption of
a multisensory feedback loop. Med Hypotheses 59:255–
260 | PubMed | ChemPort |
• di Pellegrino G, Fadiga L, Fogassi L, Gallese V, Rizzolatti G 1992
Understanding motor events: a neurophysiological study. Exp Brain Res
91:176–180 | Article | PubMed | ChemPort |
• Oberman LM, Ramachandran VS 2008 Preliminary evidence for deficits in
multisensory integration in autism spectrum disorders: the mirror neuron
hypothesis. Soc Neurosci 3:348–355
• Stein BE, Stanford TR 2008 Multisensory integration: current issues from the
perspective of the single neuron. Nat Rev Neurosci 9:255–
266 | Article | PubMed | ISI | ChemPort |
• Hardan AY, Pabalan M, Gupta N, Bansal R, Melhem NM, Fedorov S,
Keshavan MS, Minshew NJ 2009 Corpus callosum volume in children with
autism. Psychiatry Res 174:57–61
• Coben R, Clarke AR, Hudspeth W, Barry RJ 2008 EEG power and coherence
in autistic spectrum disorder. Clin Neurophysiol 119:1002–1009
• Just MA, Cherkassky VL, Keller TA, Kana RK, Minshew NJ 2007 Functional
and anatomical cortical underconnectivity in autism: evidence from an
FMRI study of an executive function task and corpus callosum
morphometry. Cereb Cortex 17:951–961
• Allen G, Courchesne E 2001 Attention function and dysfunction in autism.
Front Biosci 6:D105–D119
• Talsma D, Senkowski D, Soto-Faraco S, Woldorff MG 2010 The multifaceted
interplay between attention and multisensory integration. Trends Cogn Sci
• Posner MI, Petersen SE 1990 The attention system of the human brain. Annu
Rev Neurosci 13:25–42 | Article | PubMed | ISI | ChemPort |
• Gazzaley A, Cooney JW, McEvoy K, Knight RT, D'Esposito M 2005 Top-down
enhancement and suppression of the magnitude and speed of neural
activity. J Cogn Neurosci 17:507–517 | Article | PubMed | ISI |
• Berry AS, Zanto TP, Rutman AM, Clapp WC, Gazzaley A 2009 Practice-related
improvement in working memory is modulated by changes in processing
external interference. J Neurophysiol 102:1779–1789
• Stein BE, Meredith MA 1990 Multisensory integration. Neural and behavioral
solutions for dealing with stimuli from different sensory modalities. Ann N
Y Acad Sci 608:51–65; discussion 65 ndash; 70.
• Courchesne E, Akshoomoff NA, Townsend J, Saitoh O 1995 A model system
for the study of attention and the cerebellum: infantile autism.
Electroencephalogr Clin Neurophysiol Suppl 44:315–325
• Näätänen R 1982 Processing negativity: an evoked-potential reflection of
selective attention. Psychol Bull 92:605–640 | Article | PubMed |
• Ceponiene R, Lepisto T, Shestakova A, Vanhala R, Alku P, Naatanen R,
Yaguchi K 2003 Speech-sound-selective auditory impairment in children
with autism: they can perceive but do not attend. Proc Natl Acad Sci U S A
• Tecchio F, Benassi F, Zappasodi F, Gialloreti LE, Palermo M, Seri S, Rossini
PM 2003 Auditory sensory processing in autism: a
magnetoencephalographic study. Biol Psychiatry 54:647–654
• Jansson-Verkasalo E, Ceponiene R, Kielinen M, Suominen K, Jantti V, Linna
SL, Moilanen I, Naatanen R 2003 Deficient auditory processing in children
with Asperger Syndrome, as indexed by event-related potentials. Neurosci
Lett 338:197–200
• Oram Cardy JE, Flagg EJ, Roberts W, Roberts TP 2005 Delayed mismatch
field for speech and non-speech sounds in children with autism.
Neuroreport 16:521–525
• Kasai K, Hashimoto O, Kawakubo Y, Yumoto M, Kamio S, Itoh K, Koshida I,
Iwanami A, Nakagome K, Fukuda M, Yamasue H, Yamada H, Abe O, Aoki
S, Kato N 2005 Delayed automatic detection of change in speech sounds
in adults with autism: a magnetoencephalographic study. Clin
Neurophysiol 116:1655–1664
• Gomot M, Blanc R, Clery H, Roux S, Barthelemy C, Bruneau N. Candidate
electrophysiological endophenotypes of hyper-reactivity to change in
autism. J Autism Dev Disord, [epub ahead of print]
• Gomot M, Giard MH, Adrien JL, Barthelemy C, Bruneau N 2002
Hypersensitivity to acoustic change in children with autism:
electrophysiological evidence of left frontal cortex dysfunctioning.
Psychophysiology 39:577–584
• Gomot M, Bernard FA, Davis MH, Belmonte MK, Ashwin C, Bullmore ET,
Baron-Cohen S 2006 Change detection in children with autism: an
auditory event-related fMRI study. Neuroimage 29:475–484
• Mottron L, Burack JA, Stauder JE, Robaey P 1999 Perceptual processing
among high-functioning persons with autism. J Child Psychol Psychiatry
• Heaton P 2003 Pitch memory, labelling and disembedding in autism. J Child
Psychol Psychiatry 44:543–551
• Belmonte MK, Yurgelun-Todd DA 2003 Functional anatomy of impaired
selective attention and compensatory processing in autism. Brain Res
Cogn Brain Res 17:651–664
• Lepistö T, Kajander M, Vanhala R, Alku P, Huotilainen M, Näätänen R, Kujala
T 2008 The perception of invariant speech features in children with
autism. Biol Psychol 77:25–31
• Lepistö T, Kujala T, Vanhala R, Alku P, Huotilainen M, Näätänen R 2005 The
discrimination of and orienting to speech and non-speech sounds in
children with autism. Brain Res 1066:147–157
• Kemner C, Verbaten MN, Cuperus JM, Camfferman G, Van Engeland H 1994
Visual and somatosensory event-related brain potentials in autistic
children and three different control groups. Electroencephalogr Clin
Neurophysiol 92:225–237
• Polich J 2007 Updating P300: an integrative theory of P3a and P3b. Clin
Neurophysiol 118:2128–2148
• Novick B, Kurtzberg D, Vaughn HGJr 1979 An electrophysiologic indication of
defective information storage in childhood autism. Psychiatry Res 1:101–
• Townsend J, Westerfield M, Leaver E, Makeig S, Jung T, Pierce K,
Courchesne E 2001 Event-related brain response abnormalities in autism:
evidence for impaired cerebello-frontal spatial attention networks. Brain
Res Cogn Brain Res 11:127–145 | Article | PubMed |
• Verbaten MN, Roelofs JW, van Engeland H, Kenemans JK, Slangen JL 1991
Abnormal visual event-related potentials of autistic children. J Autism Dev
Disord 21:449–470
• Teder-Sälejärvi WA, Pierce KL, Courchesne E, Hillyard SA 2005 Auditory
spatial localization and attention deficits in autistic adults. Brain Res Cogn
Brain Res 23:221–234
• Ciesielski KT, Knight JE, Prince RJ, Harris RJ, Handmaker SD 1995 Eventrelated
potentials in cross-modal divided attention in autism.
Neuropsychologia 33:225–246



In the News

  • Amazing Results with The SAVE Program Amazing Results with The SAVE Program
  • Naples Student Benefits from The SAVE Program Naples Student Benefits from The SAVE Program
  • THE Save Program THE Save Program New treatment options for the symptoms of ADD, ADHD, Autism, Aspergers.