Encyclopedia of Autism Spectrum Disorders

2013 Edition
| Editors: Fred R. Volkmar


Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-1698-3_648


Perception includes the selection, organization, and interpretation of external information coming from the senses up to a complete representation of a stimulus. The extraction of elementary features within primary cortical receiving areas in each sensory modality is called low-level perception. It is domain general such that the same mechanisms are involved in processing social and nonsocial information. At a higher level of integration, there is pattern construction in which elementary features (e.g., of visual or auditory stimuli) are grouped into basic configurations. Visual motion perception depends on information integrated at various levels of the processing hierarchy: first-order motion is perceived in primary areas, while second-order motion requires a network of associative regions. High-level perception involves the matching of constructed configurations with memorized templates as the hierarchy of perceptual processing becomes gradually more domain specific. In turn, domain-specific perception includes face and emotion perception, language perception, and, for dynamic information, perception of biological motion.

Perception typically feeds to and receives information from other major functions in the cognitive architecture, including emotion, language, memory, attention, expectations, and conscious reasoning. Thus, perceptual configurations may be associated with innate or memorized patterns of biological significance, pattern construction is influenced by language categories, and pattern recognition involves an active comparison of perceived and stored configurations. Perception is a dynamic process which modifies (bottom-up) and is modified by (top-down) higher-level cognitive processes.

Historical Background

Kanner’s initial writings emphasized autistics’ attention to and production of perceptual information (e.g., gazing at moving objects, lining up objects by color) as essential elements of autistic repetitive movements and behaviors. He vividly described extraordinary autistic achievements in memory, construction, and attention to detail. Perception-based behaviors, he noted, were associated with extreme emotions, such as being “ecstatic” while watching spinning objects or displaying panic in response to sounds. In his later writing, Kanner (1965, p. 412) underlined that being “so concerned with the external world that they watch (it) with tense alertness to make sure that their surroundings remain static (…) in full photographic and phonic identity” is inconsistent with the withdrawal into one’s own world implied by the label autism.

Early models such as perceptual inconstancy (Ornitz, 1973) were formed around the apparently paradoxical co-occurrence, within the same modality, of overt hypo- and hyperreactions to perceptual information (e.g., to voices and vacuum cleaners, respectively). Atypical social and nonsocial representations were linked to subcortical abnormalities distorting perceptual input. However, absence of replicated brainstem event-related potential (ERP) abnormalities coupled with lack of empirical confirmation that perception in autism is unstable led to these models being abandoned in the early 1980s.

Meanwhile, early studies by Hermelin, O’Connor, and Frith in the 1960s and 1970s (Hermelin & O’Connor, 1970; Frith & Hermelin, 1969) established alternatively the absence of gross abnormalities in low-level processing. Performance in pattern reproduction, recognition, and memory was therefore considered to be unremarkable in autism. These studies were focused on the detection and imposition of a structure on visual or verbal materials, corresponding partly to pattern construction and partly to what would be now called top-down influence on perception. They concluded that autistic cognition was skewed toward meaningless or raw information, while structure imposition and recoding were diminished or absent. However, examples brought to support these positions – hyperlexia, echolalia, and 3-D drawing – implied pattern manipulation and not raw material. A decisive synthesis by Frith and Baron-Cohen (1987) concluded that “low level processes are intact in autistic children” (p. 98) and “what appear to be signs of a lower level dysfunction can be explained more powerfully in terms of a higher level cognitive dysfunction” (p. 87).

Those two conclusions, that autistic perception was unremarkable and that apparent atypicalities resulted from higher level impairment, dominated autism research for two ensuing decades, including by influencing the interpretation of autistic perceptual strengths. When administering visuospatial tasks, autistics were found to perform better than predicted by their other abilities and better than groups of intellectually disabled individuals matched on apparent IQ. In testing with Wechsler scales of intelligence, Rutter (1966) reported superior autistic performance in the block design subtest, which is based on visuospatial abilities. In 1983, this early accidental finding was extended by Shah and Frith in a deliberate investigation of autistics’ performance on the embedded figure task, which is also based on perception and manipulation of visual patterns. Autistics performed at a level superior to that predicted by their IQ (Shah & Frith, 1983).

The weak central coherence (WCC) model, elaborated by Frith (and later, with Happé) starting in the late 1980s, accounted for such autistic peaks in performance by positing a causal deficit: autistics were not displaying atypical perceptual strengths but a failure to form global or high-level representations. WCC-based interpretations were consistent in direction with the period’s cognitive research, which in the 1980s and 1990s remained oriented toward multiple high-level processing deficits, such as deficits in theory of mind, executive functioning, and complex tasks in general. In addition, Minshew’s group discouraged diagnostic use of perceptual peaks by emphasizing that they were not found in all autistics. Fine-grained research on autistic perception emerged in the 1990s as a minority current.

The tenets of WCC were questioned in 1993 in the first study extensively investigating visual perception in an autistic adult, according to the concepts and instruments of cognitive neuropsychology at the time (Mottron & Belleville, 1993). The local–global hierarchical aspect of visual perception was atypical in the form of greater interference from local to global levels and random access to features of perceptual representation but without deficits in pattern construction. Findings inconsistent with WCC-predicted deficits in auditory and visual pattern construction at the group level, together with discoveries of superior discrimination of low-level visual arrangements (Plaisted, O’Riordan, & Baron-Cohen, 1998) and superior pitch processing (Heaton, Hermelin, & Pring, 1998), then led to the enhanced perceptual functioning (EPF) model. This model originally aimed to relocate autistic perceptual peaks within an overall enhanced activity and performance of the perceptual system, including enhanced pattern construction mechanisms. However, EPF did not initially question Frith’s or Minshew’s preconception that autistics’ overall superior perceptual performance was a secondary consequence of deficits in high-level processes. This step was accomplished in an update of EPF (Mottron, Dawson, Soulieres, Hubert, & Burack, 2006) based on the blossoming of studies on perception in autism after 2000.

The updated EPF model proposed that autism is characterized by enhanced perceptual performance in low-level (e.g., pitch processing) and mid-level (e.g., pattern detection) perception, enhanced autonomy of perception toward nonperceptual systems (emotional and higher-order architecture), and enhanced role of perception in higher cognitive processes (e.g., enhanced role of perception in intelligence and in social tasks). In other words, enhanced perception in autism was therefore proposed as such, rather than as evidence for speculated high-level deficits. Multiple other groups (including A. Bertone, P. Heaton, R. Joseph, C. Kemner, E. Pellicano, K. Plaisted, E. Milne, N. Minshew, & P. Mitchell) now investigate the relation between low-level perceptual processing and various aspects of autistic cognition.

Distant from the expanding interest in research, the importance of perception has also evolved within formal autism diagnostic criteria. Autism in DSM-III included indirect reference to perception-guided repetitive behaviors: “Bizarre responses to various aspects of the environment, e.g., resistance to change, peculiar interest in or attachments to animate or inanimate objects.” DSM-III-R referred to “Persistent preoccupation with parts of objects (for example, sniffing or smelling objects, repetitive feeling of texture of materials, spinning wheels of toy cars)” and DSM-IV to “Persistent preoccupation with parts of objects.” Perceptual issues are now explicitly included in DSM-5 draft, albeit as “unusual sensory behaviors.” Perception-related behaviors are included in ADI-R and ADOS-G diagnostic instruments as atypical positive and negative reactions to sensory information (“unusual sensory interest,” “undue general sensitivity to noise,” and “abnormal, idiosyncratic, negative response to sensory stimuli”) or as repetitive behaviors possibly related to perception, as in “repetitive use of objects, hand and finger mannerisms.”

Current Knowledge

Perception-Related Behaviors

Perception-related behaviors are usually investigated under the overgeneral definitions of “repetitive” or “sensory” behaviors and by means of wide-ranging scales (e.g., Infant Toddler Sensory Profile; Dunn, 2002) using a posteriori scoring in natural, nonempirical settings, with imprecise behavior definitions (e.g., scoring a behavior as present or absent). Their reported lack of specificity and poor sensitivity therefore reflect major methodological issues (Rogers & Ozonoff, 2005). In a limited number of cases, studies of perception-related behaviors in empirical settings or using strict definitions have provided evidence regarding their specificity to autism and mechanisms involved in these behaviors. This is the case for atypical visual exploratory behaviors and lateral glances, which are linked to periodic motion (Mottron et al., 2007) and nonrandom visual (geometric) or multimodal (audiovisual synchrony) structures (Klin, Lin, Gorrindo, Ramsay, & Jones, 2009); and for shorter visual fixations to and faster disengagement from face images, which are associated with an absence of a mandatory bias for faces (Chawarska, Volkmar, & Klin, 2010).

Psychophysical Studies of Low-Level Perceptual Processing

The lowest levels of cortical visual processing, located in V1, include perception of first-order luminance-defined information, to which autistics show enhanced sensitivity compared to nonautistics, when detecting orientation of gratings. Six-month-old siblings of autistic spectrum children also demonstrate enhanced sensitivity to luminance-defined stimuli. Whereas autistics appear to discriminate high and low spatial frequencies at the same level behaviorally as nonautistics, EEG and fMRI reveal between-group differences in brain activity, mainly during high spatial frequency processing. Visual stimuli that fall within the mid-frequency range may be processed using the same mechanisms as those devoted to the processing of high spatial frequency information, providing EEG correlates for the autistic “local bias” evident in pattern analysis. At a higher level of integration, crowding is the deleterious influence of nearby contours on visual discrimination of a target, attributed to lateral inhibitory interaction of neurons encoding visual properties of nearby distracters. Diminished crowding effects, for which there is preliminary evidence in autism, may allow enhanced segregation of a target from close distracters, offering an explanation for superiorities in visual search.

Autistics have demonstrated atypicalities in some low-level but integrative tasks (Bertone, Mottron, Jelenic, & Faubert, 2005), but as of now, findings are insufficiently homogeneous to posit a deficit in integration. Second-order texture-generated perception requires an integration of primary V1 and associative brain regions V2/V3. The threshold for discriminating the orientation of static second-order gratings is elevated in autism. Early local “binding” mechanisms of contour integration have been investigated, in a search for the lowest-level indication of a putative deficit in grouping processes. However, most recent studies using this method have shown typical behavioral performance in autism, although electrophysiological investigations of contour integration reveal processing differences between autistics and nonautistics. Colors are processed in a complex stream (V1, V2, V4, V8), as second-order visual information, and careful studies show diminished discrimination performance at this level in autistics compared to nonautistics. Components of motion perception, which involve areas V1, V2, and V5/MT, have been studied thoroughly, based on initial findings of diminished influence of perceived motion (optical flow) on postural control and higher thresholds for global motion coherence. When motion perception is decomposed according to the neural complexity required to perceive the motion, perception of first-order motion is preserved, but second-order motion is diminished. Motion coherence tasks measure the ratio of dots within a dot set that have to move together in order to produce a perception of movement, and this perception specifically requires the middle temporal (MT) area. Most recent studies report no group differences, but the variability of results for motion coherence does not permit firm conclusions with respect to its typicality in autism or its influence on overt behaviors. Sporadically reported autistic differences may result from atypical feeding of information from lower levels and may not be motion specific. Overall there are multiple sources of evidence for atypical low-level visual perceptual processing in autism, some being associated with enhanced behavioral performance, but low-level causative roles in superiorities in pattern detection and manipulation remain to be specified.

In the auditory modality, multiple types of tasks involving pitch perception are performed at a superior level by autistics, representing one of the most replicated areas of autistic superior performance. Task types have included discriminating and categorizing pitches, mapping tonal intervals in a visual schema, memorizing tone-picture associations, determining the direction of pitch-interval correspondence, detecting a named pitch within a chord, memorizing isolated tones and sequences of tones, and detecting a deviant pitch in a sequence of complex sounds. Absolute pitch is considerably more frequent in autistic than nonautistic individuals and, frequently but not always, is associated with savant musical ability. Superior pitch processing has been observed in autistics with or without intellectual disability (according to various measures) but is more frequently observed in autistics whose measured intelligence is in the normal range and who have a history of speech delay.

There are currently no behavioral task findings involving nonsocial simple or complex sounds and a matched group that demonstrate a deficit in autistics. The predicted auditory parallel with possibly diminished processing of second-order visual information has not been found. Robustness of superior pitch processing in autism is confirmed by event-related potentials, which also indicate enhanced detection of pitch changes, mostly in the form of shorter mismatch negativity, shorter latency, or enhanced amplitude. Enhanced low-level auditory perception has a firmly established relation with frequent giftedness in music as well as with atypical language processing and behaviorally observed speech delay.

Other modalities – tactile, olfactory, and taste – have not yet been sufficiently studied to allow any conclusive report. Multimodal integration, which was prematurely considered to be dysfunctional, results in behaviorally normal performance by autistics for integration of low-level perceptual stimuli. However, autistics’ verbal labeling of audiovisual integrative patterns may demonstrate sporadic, variable atypicalities.

Cognitive Studies on Pattern Detection, Construction, and Manipulation

Autistics display enhanced performance in tasks requiring detection of a pre-identified local target embedded in a larger probe. Visual search tasks typically consist of detecting the presence or absence of an item among a series of distractors sharing one or several features with the target. The superiority of autistics in visual search is well replicated, encompassing shorter visual fixations, superior discrimination of targets, as well as parallel processing of a larger number of distractors than controls (Caron, Mottron, Berthiaume, & Dawson, 2006). Embedded Figures Task (EFT) consists of detecting a simple figure hidden within a complex one. Here also autistics demonstrate a well-replicated superior performance, mostly in the form of increased speed. Another type of task, using hierarchical stimuli, also reveals increased detection of local targets and diminished bias for processing global aspects of a pattern in autistics. Hierarchical or Navon stimuli are typically large “global” letters, numbers, or geometric shapes, composed of small “local” elements, such as a big H composed of small Bs. The task consists of detecting, naming, or matching a component situated at either global (e.g., H) or local levels (e.g., B). Autistics can show more accurate local target detection than typical individuals, while global-level stimuli reaction times are more affected, compared to those of typical individuals, by incongruent local stimuli. In the auditory modality, with musical hierarchical stimuli, autistics reliably display a typical global advantage but either a superior detection of local changes or a diminished global to local interference.

Pattern construction and manipulation are also autistic strengths, first quantitatively reported in Wechsler block design. In this task, the participant has to reproduce a red and white geometric design with a set of red, white, and bicolor blocks. Autistics usually perform one to three SDs above their level of IQ, and they outperform controls both in accuracy and RT. In autism, a block design (BD) peak is associated with the presence of speech delay. The BD peak has two proposed sources, enhanced perception (e.g., autistics with BD peak are also superior in visual memory, visual search, and discrimination) and diminished mandatory influence of global aspects of the figure to be reproduced on local parts matching and manipulation. Superior performance in mental rotation tasks in autistics also suggests enhanced construction and manipulation of mental images, which in turn may be attributed to an overall superiority in perceptual performance and to a particular strength in veridical mapping, the ability to efficiently detect isomorphisms among entities and make correspondence between these isomorphic features.

Domain-Specific Perception: Biological Motion, Faces, and Language

Biological motion tasks consist in recognizing typical human or animal activity from point-light displays. Although the verbal labeling of the motion may be less salient or less automatically produced by autistics, a large fraction of studies have found typical perceptual performance at this level. An fMRI study reporting both similarities and differences in task performance suggests in autistics a diminished involvement of the superior temporal sulcus (STS), an associative region considered central for perception of biological motion in nonautistics.

Atypical overt behaviors toward human faces are diagnostically important in autism. Face processing has therefore been the focus of intense research interest in the past 40 years, yet results are surprisingly tenuous. Following early experiments suggesting a domain-general local bias, and based on perceptual theories of autism, research on face perception in autism has often focused on the processing of holistic versus local properties of face images. Empirical strategies have included comparison of impact of low- versus high-pass filtering on face image processing, inversion effects including the Thatcher illusion, composite face effects, natural versus nonnatural segmentation of face images, and effects of face context on face part recognition. No clear autistic deficit in the processing of holistic aspects of face images has been found; for example, autistics can display typical face inversion effects, even if not under all experimental conditions. In contrast, there are indications of superior use of face parts for further processing of face images, consistent with an amodal and domain-general local orientation. Typical performance may be obtained through an equalization of relative informative values of low and high spatial frequencies (Simmons et al., 2009).

Studies of ERP responses similarly do not overall indicate an autistic deficit in face processing. Differences reported between responses to face and object manipulation are observed in autistics, indicative of diminished specialization or category specificity. In the same direction, a meta-analysis of regions involved in face-processing tasks indicates that despite activity in typical face-processing regions, other regions are active only in autistics. Autistics show, for example, greater activity bilaterally in extrastriate (BA 18, 19) and striate (BA 17) cortex compared to nonautistics when processing face images (Samson, Mottron, Soulières, & Zeffiro, 2011).

In sum, it cannot be stated, as was routinely written in the previous decade, that autistics are characterized by a face-processing deficit in that their performance in perceptual tasks involving face images has been comparable to that of nonautistics in most of the tasks used. The ability to use specific parts for face recognition cannot accurately be reduced to a simple deficit; instead, autistics are less strategic and more versatile when scanning faces for whatever purpose. Face processing in autistics seems to rely on a large network of occipital and temporal areas specifically responsive to certain visual categories in nonautistics.

Atypicalities in speech development and behaviors when exposed to vocalizations are key diagnostic features of a large fraction of the autistic spectrum, such that one could expect perceptual processing of speech to be precociously impaired. The most reliable finding on the relation between auditory perception and speech processing is the coexistence of speech delay in infancy and superior pitch processing at an adult age, albeit the latter is not predictive of speech level at an adult age. Behaviorally, discrimination of the physical aspect of speech (pitch contour) may be superior in autistics, whereas nonautistics cannot attend to a physical property of an auditory pattern without being distracted by its linguistic dimension (Jarvinen-Pasley, Wallace, Ramus, Happé, & Heaton, 2008). A perceptual component may be implicated in the reported difficulty in speech recognition in noise or atypicalities in prosody perception. In terms of material-specific cortical specialization, a reduced leftward asymmetry has been reliably observed for speech processing. Discrimination and orientation to spectrally and temporally complex speechlike material results in atypical, generally diminished brain activity for ERP components indicative of attention to sounds. Autistics exhibit diminished activity in nonprimary auditory cortex and increased activity in primary auditory cortex in response to the presentation of temporally, but not of spectrally complex sounds. Greater temporal complexity effects in primary auditory regions sensitive to acoustic features and reduced temporal complexity effects in auditory regions sensitive to more abstract sound features could represent a greater focus toward perceptual aspects of speech sounds in autism.

Relation with Other Elements of the Cognitive Architecture

Perception is a multilevel system that provides information to but also receives information from multiple other components in the cognitive architecture. Both feedforward and feedback influences involving perception present some atypicalities in autistics. For example, in nonautistics, feedback from pattern formation to low-level perception sometimes produces visual illusions and distortions. In a visual illusion, the judgment on properties of a visuospatial element is altered by its inclusion in a larger visual context. Autistics display less (but still some) susceptibility to some visual illusions when compared to typical individuals. Categorical perception also produces distortions in nonautistics, as feedback influences from learned categories alters the saliency of perceptual properties of a stimulus. Despite similar categorization abilities, autistics’ discrimination is less influenced by categorical knowledge.

There are indications that in autism, visual perception plays a superior role in high-level cognitive processes, which are more language-mediated in nonautistics. For example, lateral glances toward faces and prolonged lateral inspections of rotating objects influence the course of directed attention in autistic toddlers. One of the strongest findings in autistic visual perception, robust enough to be valid across tasks, is revealed by a functional imaging meta-analysis of all tasks implicating visually presented material, in which autistics present superior activity across a broad expanse of brain regions involved in visual perception and perceptual expertise. This suggests that perception plays a superior role in complex cognitive operations – encompassing language, problem-solving, reasoning, etc. – with effects on performance that are not necessarily detrimental and are sometimes beneficial (Samson et al., 2011).

Connections and influences between perceptual brain regions and other brain regions have recently been studied through investigations of structural and functional connectivity. Six structural studies included the visual cortex, all of them reporting altered connectivity in the direction of a diminished integrity of white matter fibers in autistics compared to nonautistics. Despite the small number of studies and the variability in the participants’ diagnoses and age, these investigations revealed that visual areas are atypically connected mainly to regions in the temporal lobes but also in frontal and parietal lobes. Task-related functional connectivity studies mainly show results in the same direction, that is, less correlation between the activity of visual areas and other cortical regions in the frontal, parietal, or temporal lobes, during a wide range of tasks.


Atypical autistic perception was one of the key elements of Kanner’s seminal description. The early accounts of perception in autism hypothesized either an abnormal and inconsistent distorting of perceptual input or, alternatively, an unremarkable perception, producing a raw, uncoded representation of the world. First accounts of perception-related behaviors concluded that there was a lack of specificity compared to other neurodevelopmental conditions. The role of these behaviors in diagnosis was minimized, as they were merged with other repetitive behaviors in DSM definitions of autism.

Within the last two decades, these views have profoundly changed. There is now a consensus that the autistic visual and auditory systems provide the rest of the brain with qualitatively, and quantitatively, different information than in nonautistics. Superior performances in nonsavant auditory perception have as yet mainly been found through investigations limited to low-level processes. However, wider-ranging studies have revealed that superior performances in visual perception often imply pattern detection and manipulation, indicating that autistic perception does not produce a raw, uncoded representation of the world. In both modalities, peaks in perception can be correlated with speech delay, suggesting a relation between the two factors. Relations with nonperceptual components of the autistic cognitive architecture are asymmetrical. On the one hand, perception is more autonomous with regard to emotions, expectations, and language-mediated processes. Autistic perception is more veridical and immune to distortions resulting from top-down influences than in typical individuals. On the other hand, superior brain activity in perceptual associative visual areas is evident in a large array of tasks, suggesting that perception plays a superior role in complex, language-loaded, intelligent cognitive operations, without mandatory detrimental effects on performance.

Concerning relations between perception and other areas of atypicality, autistic perception cannot be straightforwardly explained by cognitive models focused on high-level processes: “perceptual alterations are present in ASD, independent of social function” (Behrman, Thomas, & Humphreys, 2006, p.263). However, non material-specific peculiarities in perception have the potential to explain autistic characteristics in the diagnostic sociocommunicative as well as in the repetitive behaviors and restricted interests domains. This potential remains underexplored, but there is growing recognition of the “great need for further exploration” of fundamental low-level perceptual atypicalities in autism (Belmonte et al., 2004, p. 658).

Future Directions

  • The cartography of autistic low-level perceptual processes is far from complete. Still to be sufficiently investigated are the following: in vision, contrast and (to a lesser extent) colors; and in audition, lateral inhibition, inspection time, among others.

  • Multiple auditory equivalents of visuospatial peaks have not yet been investigated.

  • The aggregation of auditory and visual perceptual peaks in the same individual is yet unknown.

  • The biological substrates, at the cellular level, of enhanced discrimination of low-level information (e.g., pitch) are unknown.

  • The role of access to and atypical use of (e.g., overtraining with) materials or information in the genesis of autistic perceptual profiles has not been investigated.

  • What is the relation between actual or proposed delineations of the autistic phenotype and perceptual characteristics?

See Also

References and Readings

  1. Behrmann, M., Thomas, C., & Humphreys, K. (2006). Seeing it differently: Visual processing in autism. Trends in Cognitive Sciences, 10(6), 258–264.PubMedGoogle Scholar
  2. Belmonte, M. K., Cook, E. H., Jr., Anderson, G. M., Rubenstein, J. L., Greenough, W. T., Beckel-Mitchener, A., et al. (2004). Autism as a disorder of neural information processing: Directions for research and targets for therapy. Molecular Psychiatry, 9(7), 646–663.PubMedGoogle Scholar
  3. Bertone, A., Mottron, L., Jelenic, P., & Faubert, J. (2005). Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity. Brain, 128(Pt 10), 2430–2441.PubMedGoogle Scholar
  4. Caron, M. J., Mottron, L., Berthiaume, C., & Dawson, M. (2006). Cognitive mechanisms, specificity and neural underpinnings of visuospatial peaks in autism. Brain, 129(Pt 7), 1789–1802.PubMedGoogle Scholar
  5. Chawarska, K., Volkmar, F., & Klin, A. (2010). Limited attentional bias for faces in toddlers with autism spectrum disorders. Archives of General Psychiatry, 67(2), 178–185.PubMedGoogle Scholar
  6. Dunn, W. (2002). Infant-toddler sensory profile: User’s manual. Therapy skill builders. San Antonio, TX: Psychological Corporation.Google Scholar
  7. Frith, U., & Baron-Cohen, S. (1987). Perception in autistic children. In D. J. Cohen, A. Donnellan, & R. Paul (Eds.), Handbook of autism and pervasive developmental disorders. New York: Wiley.Google Scholar
  8. Frith, U., & Hermelin, B. (1969). The role of visual and motor cues for normal, subnormal and autistic children. Journal of Child Psychology and Psychiatry, 10, 153–163.PubMedGoogle Scholar
  9. Heaton, P., Hermelin, B., & Pring, L. (1998). Autism and pitch processing: A precursor for savant musical ability? Music Perception, 15(3), 291–305.Google Scholar
  10. Hermelin, B., & O’Connor, N. (1970). Psychological experiments with autistic children. Oxford: Pergamon Press.Google Scholar
  11. Jarvinen-Pasley, A., Wallace, G. L., Ramus, F., Happe, F., & Heaton, P. (2008). Enhanced perceptual processing of speech in autism. Developmental Science, 11(1), 109–121.PubMedGoogle Scholar
  12. Kanner, L. (1965). Infantile autism and the schizophrenias. Behavioral Science, 10(4), 412–420.PubMedGoogle Scholar
  13. Klin, A., Lin, D. J., Gorrindo, P., Ramsay, G., & Jones, W. (2009). Two-year-olds with autism orient to non-social contingencies rather than biological motion. Nature, 459(7244), 257–261.PubMedGoogle Scholar
  14. Mottron, L., & Belleville, S. (1993). A study of perceptual analysis in a high-level autistic subject with exceptional graphic abilities. Brain and Cognition, 23(2), 279–309.PubMedGoogle Scholar
  15. Mottron, L., Dawson, M., Soulieres, I., Hubert, B., & Burack, J. (2006). Enhanced perceptual functioning in autism: An update, and eight principles of autistic perception. Journal of Autism and Developmental Disorders, 36(1), 27–43.PubMedGoogle Scholar
  16. Mottron, L., Mineau, S., Martel, G., Bernier, C. S., Berthiaume, C., Dawson, M., et al. (2007). Lateral glances toward moving stimuli among young children with autism: Early regulation of locally oriented perception? Development and Psychopathology, 19(1), 23–36.PubMedGoogle Scholar
  17. Ornitz, E. M. (1973). Childhood autism. A review of the clinical and experimental literature. California Medicine, 118(4), 21–47.PubMedGoogle Scholar
  18. Plaisted, K., O’Riordan, M., & Baron-Cohen, S. (1998). Enhanced discrimination of novel, highly similar stimuli by adults with autism during a perceptual learning task. Journal of Child Psychology and Psychiatry, 39(5), 765–775.PubMedGoogle Scholar
  19. Rogers, S. J., & Ozonoff, S. (2005). Annotation: What do we know about sensory dysfunction in autism? A critical review of the empirical evidence. Journal of Child Psychology and Psychiatry, 46(12), 1255–1268.PubMedGoogle Scholar
  20. Rutter, M. (1966). Behavioural and cognitive characteristics of a series of psychotic children. In L. Wing (Ed.), Early childhood autism: Clinical, educational and social aspects (pp. 51–81). Oxford: Pergamon Press.Google Scholar
  21. Samson, F., Mottron, L., Soulieres, I., & Zeffiro, T. A. (2011). Enhanced visual functioning in autism: An ALE meta-analysis. Human Brain Mapping. doi:10.1002/hbm.21307. [Epub ahead of print].Google Scholar
  22. Shah, A., & Frith, U. (1983). An islet of ability in autistic children: A research note. Journal of Child Psychology and Psychiatry, 24(4), 613–620.PubMedGoogle Scholar
  23. Simmons, D. R., Robertson, A. E., McKay, L. S., Toal, E., McAleer, P., & Pollick, F. E. (2009). Vision in autism spectrum disorders. Vision Research, 49(22), 2705–2739.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Center of Excellence in Pervasive Developmental Disorders of University of MontrealQCCanada
  2. 2.Department of PsychiatryRiviere-des-Prairies Hospital, University of MontrealMontrealCanada
  3. 3.Centre d’excellence en troubles envahissants du développement de l’université de MontréalHôpital Rivière-des-PrairiesMontréalCanada
  4. 4.Centre d’excellence en troubles envahissants du développement de l’université de MontréalHôpital Rivière-Des-PrairiesMontréalCanada