An early origin for detailed perception in Autism Spectrum Disorder: biased sensitivity for high-spatial frequency information.

Abstract

Autistics demonstrate superior performances on several visuo-spatial tasks where local or detailed information processing is advantageous. Altered spatial filtering properties at an early level of visuo-spatial analysis may be a plausible perceptual origin for such detailed perception in Autism Spectrum Disorder. In this study, contrast sensitivity for both luminance and texture-defined vertically-oriented sine-wave gratings were measured across a range of spatial frequencies (0.5, 1, 2, 4 & 8 cpd) for autistics and non-autistic participants. Contrast sensitivity functions and peak frequency ratios were plotted and compared across groups. Results demonstrated that autistic participants were more sensitivity to luminance-defined, high spatial frequency gratings (8 cpd). A group difference in peak distribution was also observed as 35% of autistic participants manifested peak sensitivity for luminance-defined gratings of 4 cpd, compared to only 7% for the comparison group. These findings support that locally-biased perception in Autism Spectrum Disorder originates, at least in part, from differences in response properties of early spatial mechanisms favouring detailed spatial information processing.

The developmental trajectory of contrast sensitivity in autism spectrum disorder

“…For the high spatial frequency condition, group trajectories were centered from 6, 10, and 13 years to determine if mean sensitivity for 8 cpd diverged and/or converged in school‐ages, late childhood, and adolescence. Given recent findings demonstrating an increased sensitivity to 8 cpd in adults with ASD [Kéïta et al, ], analyses in this group of younger participants aimed to establish whether a similar or different pattern appeared earlier in development. It is important to note, however, that the rate of development of sensitivity at 8 cpd remained statistically similar across groups, regardless of the age at which the analysis was centered, F (1,85) = 0.63, P = 0.429, partial η 2 = 0.007 (Group × Age interaction).…”

“…A recent study using a comparable approach in adolescents and adults with a strict diagnosis of Autistic Disorder based on the Diagnostic and Statistical Manual of Mental Disorders IV‐TR [American Psychiatric Association, ] revealed an increased sensitivity to high spatial frequency information (i.e., 8 cpd) [Kéïta, Guy, Berthiaume, Mottron, and Bertone, ]. Electrophysiological studies examining neural responses to spatial frequency information are in line with these findings, demonstrating atypical brain activity for the processing of high spatial frequency information in children and adults with ASD [Boeschoten, Kenemans, Van Engeland, & Kemner, ; Jemel, Mimeault, Saint‐Amour, Hosein, & Mottron, ; Milne et al, ; Pei, Baldassi, & Norcia, ; Vlamings, Jonkman, van Daalen, van der Gaag, & Kemner, ].…”

“…Contrast sensitivity functions were obtained by measuring detection thresholds to vertical, sinewave gratings of different spatial frequencies (0.5, 1, 2, 4, and 8 cpd) within a circular Gaussian envelope ( σ = 2°). These frequencies were chosen based on pilot data collected from children and previous investigations conducted in adolescents and adults with and without ASD [Kéïta et al, ]. The contrast of the gratings (i.e., the smallest luminance difference between white and dark lines of the grating) was defined by its Michelson contrast [( L max − L min )/( L max + L min ) × 100].…”

Rethinking the concepts of ‘local or global processors’: evidence from Williams syndrome, Down syndrome, and Autism Spectrum Disorders

“…See Bouvet, Simard‐Meilleur, Paignon, Mottron & Donnadieu (); Kéïta, Guy, Berthiaume, Mottron & Bertone (); Muth, Hönekopp & Falter (); Olu‐Lafe, Liederman & Tager‐Flusberg (); and Yamasaki, Maekawa, Takahashi, Fujita, Kamio et al . (), for more recent evidence.…”

A New Image Noise Detection Approach using Morphology and Partial Differential Equations

“…Many further uses of these images require that the noise will be (partially) removed -for aesthetic purposes as in artistic work or marketing, or for practical purposes such as computer vision. In real-world photographs, the highest spatial-frequency detail consists mostly of variations in brightness ("luminance detail") rather than variations in hue ("chroma detail") [5]. Since any noise reduction algorithm should attempt to remove noise without sacrificing real detail from the scene photographed, one risks a greater loss of detail from luminance noise reduction than chroma noise reduction simply because most scenes have little high frequency chroma detail to begin with.…”