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.

ASSESSING THE UNRELIABILITY OF THE MEDICAL LITERATURE: A RESPONSE TO "WHY MOST PUBLISHED RESEARCH FINDINGS ARE FALSE"

A recent article in this journal (Ioannidis JP (2005) Why most published research findings are false. PLoS Med 2: e124) argued that more than half of published research findings in the medical literature are false. In this commentary, we examine the structure of that argument, and show that it has three basic components: 1)An assumption that the prior probability of most hypotheses explored in medical research is below 50%. 2)Dichotomization of P-values at the 0.05 level and introduction of a “bias” factor (produced by significance-seeking), the combination of which severely weakens the evidence provided by every design. 3)Use of Bayes theorem to show that, in the face of weak evidence, hypotheses with low prior probabilities cannot have posterior probabilities over 50%. Thus, the claim is based on a priori assumptions that most tested hypotheses are likely to be false, and then the inferential model used makes it impossible for evidence from any study to overcome this handicap. We focus largely on step (2), explaining how the combination of dichotomization and “bias” dilutes experimental evidence, and showing how this dilution leads inevitably to the stated conclusion. We also demonstrate a fallacy in another important component of the argument –that papers in “hot” fields are more likely to produce false findings. We agree with the paper’s conclusions and recommendations that many medical research findings are less definitive than readers suspect, that P-values are widely misinterpreted, that bias of various forms is widespread, that multiple approaches are needed to prevent the literature from being systematically biased and the need for more data on the prevalence of false claims. But calculating the unreliability of the medical research literature, in whole or in part, requires more empirical evidence and different inferential models than were used. The claim that “most research findings are false for most research designs and for most fields” must be considered as yet unproven.

Low prevalence of SV40 in Swiss mesothelioma patients after elimination of false-positive PCR results

The association of simian virus 40 (SV40) with malignant pleural mesothelioma is currently under debate. In some malignancies of viral aetiology, viral DNA can be detected in the patients' serum or plasma. To characterize the prevalence of SV40 in Swiss mesothelioma patients, we optimized a real-time PCR for quantitative detection of SV40 DNA in plasma, and used a monoclonal antibody for immunohistochemical detection of SV40 in mesothelioma tissue microarrays. Real-time PCR was linear over five orders of magnitude, and sensitive to a single gene copy. Repeat PCR determinations showed excellent reproducibility. However, SV40 status varied for independent DNA isolates of single samples. We noted that SV40 detection rates by PCR were drastically reduced by the implementation of strict room compartmentalization and decontamination procedures. Therefore, we systematically addressed common sources of contamination and found no cross-reactivity with DNA of other polyomaviruses. Contamination during PCR was rare and plasmid contamination was infrequent. SV40 DNA was reproducibly detected in only 4 of 78 (5.1%) plasma samples. SV40 DNA levels were low and not consistently observed in paired plasma and tumour samples from the same patient. Immunohistochemical analysis revealed a weak but reproducible SV40 staining in 16 of 341 (4.7%) mesotheliomas. Our data support the occurrence of non-reproducible SV40 PCR amplifications and underscore the importance of proper sample handling and analysis. SV40 DNA and protein were found at low prevalence (5%) in plasma and tumour tissue, respectively. This suggests that SV40 does not appear to play a major role in the development of mesothelioma.

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.

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.