Abnormal Speech Spectrum and Increased Pitch Variability in Young Autistic Children

Children with autism spectrum disorder (ASD) who can speak often exhibit abnormal voice quality and speech prosody, but the exact nature and underlying mechanisms of these abnormalities, as well as their diagnostic power are currently unknown. Here we quantified speech abnormalities in terms of the properties of the long-term average spectrum (LTAS) and pitch variability in speech samples of 83 children (41 with ASD, 42 controls) ages 4–6.5 years, recorded while they named a sequence of daily life pictures for 60 s. We found a significant difference in the group's average spectra, with ASD spectra being shallower and exhibiting less harmonic structure. Contrary to the common impression of monotonic speech in autism, the ASD children had a significantly larger pitch range and variability across time. A measure of this variability, optimally tuned for the sample, yielded 86% success (90% specificity, 80% sensitivity) in classifying ASD in the sample. These results indicate that speech abnormalities in ASD are reflected in its spectral content and pitch variability. This variability could imply abnormal processing of auditory feedback or elevated noise and instability in the mechanisms that control pitch. The current results are a first step toward developing speech spectrum-based bio-markers for early diagnosis of ASD

Face Recognition: the Problem of Compensating for Changes in Illumination Direction

A face recognition system must recognize a face from a novel image despite the variations between images of the same face. A common approach to overcoming image variations because of changes in the illumination conditions is to use image representations that are relatively insensitive to these variations. Examples of such representations are edge maps, image intensity derivatives, and images convolved with 2D Gabor-like filters. Here we present an empirical study that evaluates the sensitivity of these representations to changes in illumination, as well as viewpoint and facial expression. Our findings indicated that none of the representations considered is sufficient by itself to overcome image variations because of a change in the direction of illumination. Similar results were obtained for changes due to viewpoint and expression. Image representations that emphasized the horizontal features were found to be less sensitive to changes in the direction of illumination. However, systems..

2004 Special Issue Associative learning in early vision

Sensory discriminations often improve with practice (perceptual learning). Recent results show that practice does not necessarily lead to the best possible performance on the task. It was shown that learning a task (contrast discrimination) that has already reached saturation could be enabled by a contextual change in the stimulus (the addition of surrounding flankers) during practice. Psychophysical results with varying context show a behavior that is described by a network of local visual processors with horizontal recurrent interactions. We describe a mathematical learning rule for the modification of cortical synapses that is inspired by the experimental results and apply it to recurrent cortical networks that respond to external stimuli. The model predicts that repeated presentation of the same stimulus leads to saturation of synaptic modification, such that the strengths of recurrent connections depend on the configuration of the stimulus but not on its amplitude. When a new stimulus is introduced, the modification is rekindled until a new equilibrium is reached. This effect may explain the saturation of perceptual learning when practicing a certain task repeatedly. We present simulations of contrast discrimination in a simplified model of a cortical column in the primary visual cortex and show that performance of the model is reminiscent of context-dependent perceptual learning