1. Austerweil JL. {{Contradictory « heuristic » theories of autism spectrum disorders: The case for theoretical precision using computational models}}. {Autism}. 2014.
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2. Gupta S, Ellis SE, Ashar FN, Moes A, Bader JS, Zhan J, West AB, Arking DE. {{Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism}}. {Nat Commun}. 2014; 5: 5748.
Recent studies of genomic variation associated with autism have suggested the existence of extreme heterogeneity. Large-scale transcriptomics should complement these results to identify core molecular pathways underlying autism. Here we report results from a large-scale RNA sequencing effort, utilizing region-matched autism and control brains to identify neuronal and microglial genes robustly dysregulated in autism cortical brain. Remarkably, we note that a gene expression module corresponding to M2-activation states in microglia is negatively correlated with a differentially expressed neuronal module, implicating dysregulated microglial responses in concert with altered neuronal activity-dependent genes in autism brains. These observations provide pathways and candidate genes that highlight the interplay between innate immunity and neuronal activity in the aetiology of autism.
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3. Kushki A, Khan A, Brian J, Anagnostou E. {{A Kalman Filtering Framework for Physiological Detection of Anxiety-Related Arousal in Children with Autism Spectrum Disorder}}. {IEEE Trans Biomed Eng}. 2014.
Objective: Anxiety is associated with physiological changes that can be non-invasively measured using inexpensive and wearable sensors. These changes provide an objective and language-free measure of arousal associated with anxiety, which can complement treatment programs for clinical populations who have difficulty with introspection, communication, and emotion recognition. This motivates the development of automatic methods for detection of anxiety-related arousal using physiology signals. While several supervised learning methods have been proposed for this purpose, these methods require regular collection and updating of training data and are therefore not suitable for clinical populations where obtaining labelled data may be challenging due to impairments in communication and introspection. In this context, the objective of this paper is to develop an unsupervised and realtime arousal detection algorithm. Methods: We propose a learning framework based on Kalman filtering theory for detection of physiological arousal based on cardiac activity. The performance of the system was evaluated on data obtained from a sample of children with autism spectrum disorder. Results: The results indicate that the system can detect anxietyrelated arousal in these children with sensitivity and specificity of 99% and 92%, respectively. Conclusion and significance: Our results show that the proposed method can detect physiological arousal associated with anxiety with high accuracy, providing support for technical feasibility of augmenting anxiety treatments with automatic detection techniques. This approach can ultimately lead to more effective anxiety treatment for a larger and more diverse population.
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4. Manning C, Baker DH. {{Response to Davis and Plaisted-Grant: Psychophysical data do not support the low-noise account of autism}}. {Autism}. 2014.
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5. Waite J, Moss J, Beck SR, Richards C, Nelson L, Arron K, Burbidge C, Berg K, Oliver C. {{Repetitive Behavior in Rubinstein-Taybi Syndrome: Parallels with Autism Spectrum Phenomenology}}. {J Autism Dev Disord}. 2014.
Syndrome specific repetitive behavior profiles have been described previously. A detailed profile is absent for Rubinstein-Taybi syndrome (RTS). The Repetitive Behaviour Questionnaire and Social Communication Questionnaire were completed for children and adults with RTS (N = 87), Fragile-X (N = 196) and Down (N = 132) syndromes, and individuals reaching cut-off for autism spectrum disorder (N = 228). Total and matched group analyses were conducted. A phenotypic profile of repetitive behavior was found in RTS. The majority of behaviors in RTS were not associated with social-communication deficits or degree of disability. Repetitive behavior should be studied at a fine-grained level. A dissociation of the triad of impairments might be evident in RTS.
