Facial affect recognition training in autism: can we animate the fusiform gyrus?

One of the most consistent findings in the neuroscience of autism is hypoactivation of the fusiform gyrus (FG) during face processing. In this study the authors examined whether successful facial affect recognition training is associated with an increased activation of the FG in autism. The effect of a computer-based program to teach facial affect identification was examined in 10 individuals with high-functioning autism. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) changes in the FG and other regions of interest, as well as behavioral facial affect recognition measures, were assessed pre- and posttraining. No significant activation changes in the FG were observed. Trained participants showed behavioral improvements, which were accompanied by higher BOLD fMRI signals in the superior parietal lobule and maintained activation in the right medial occipital gyrus.

The development and evaluation of a computer-based program to test and to teach the recognition of facial affect

Autism is a chronic pervasive neurodevelopmental disorder characterized by the early onset of social and communicative impairments as well as restricted, ritualized, stereotypic behavior. The endophenotype of autism includes neuropsychological deficits, for instance a lack of "Theory of Mind" and problems recognizing facial affect. In this study, we report the development and evaluation of a computer-based program to teach and test the ability to identify basic facially expressed emotions. 10 adolescent or adult subjects with high-functioning autism or Asperger-syndrome were included in the investigation. A priori the facial affect recognition test had shown good psychometric properties in a normative sample (internal consistency: rtt=.91-.95; retest reliability: rtt=.89-.92). In a prepost design, one half of the sample was randomly assigned to receive computer treatment while the other half of the sample served as control group. The training was conducted for five weeks, consisting of two hours training a week. The trained individuals improved significantly on the affect recognition task, but not on any other measure. Results support the usefulness of the program to teach the detection of facial affect. However, the improvement found is limited to a circumscribed area of social-communicative function and generalization is not ensured.

Nitric oxide synthase protein levels, not the mRNA, are downregulated in olfactory bulb interneurons of reeler mice

Homozygous mutations in the Reelin gene result in severe disruption of brain development. The histogenesis of layered regions, like the neocortex, hippocampus and the cerebellum, is most notably affected in mouse reeler mutants and similar traits are also present in mice lacking molecular components of the Reelin signalling pathway. Moreover, there is evidence for an additional role of Reelin in sustaining synaptic plasticity in adult networks. Nitric oxide is an important gaseous messenger that can modulate neuronal plasticity both in developing and mature synaptic networks and has been shown to facilitate synaptic changes in the hippocampus, cerebellum and olfactory bulb. We studied the distribution and content of neuronal nitric oxide synthase in the olfactory bulbs of reeler and wildtype mice. Immunocytochemistry reveals that Reelin and neuronal nitric oxide synthase containing interneurons are two distinct, non overlapping cell populations of the olfactory bulb. We show by in situ hybridization that both nitrergic and Reelin expressing cells represent only a subset of olfactory bulb GABAergic neurons. Immunoblots show that neuronal nitric oxide synthase protein content is decreased by two thirds in reeler mice causing a detectable loss of immunolabelled cells throughout the olfactory bulb of this strain. However, neuronal nitric oxide synthase mRNA levels, essayed by quantitative real-time RT-PCR, are unaffected in the reeler olfactory bulb. Thus, disruption of the Reelin signalling pathway may modify the turnover of neuronal nitric oxide synthase in the olfactory bulb and possibly affects nitric oxide functions in reeler mice.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.