1. Esse Wilson J, Trumbo MC, Wilson JK, Tesche CD. {{Transcranial direct current stimulation (tDCS) over right temporoparietal junction (rTPJ) for social cognition and social skills in adults with autism spectrum disorder (ASD)}}. {Journal of neural transmission (Vienna, Austria : 1996)}. 2018.
Social deficits are core to autism spectrum disorder (ASD). Current treatments are extremely time- and labor-intensive. Transcranial direct current stimulation (tDCS) may be a promising treatment modality to safely enhance treatments targeting social cognition and social skills. This pilot study investigates the effectiveness of social skills treatment interventions paired with anodal tDCS for six adults 18-58 years with ASD. Differences were predicted on the verbal fluency (VF) test and a test of social skills (TASSK-M) for verum (2.0 mA) vs. sham tDCS, which was randomly assigned in a within-subjects, double-blinded design in adults with ASD with normal or higher cognitive functioning. The anode electrode was placed over right temporoparietal (CP6) and cathode over ipsilateral deltoid. Wilcoxon signed-rank tests for paired data indicated that participants received a significantly higher score on the VF test after receiving verum tDCS compared to sham tDCS, with no significant differences found on the TASSK-M. Post-hoc analysis showed that the emotion-word portion of the VF test, specifically, indicated significant differences when comparing verum to sham tDCS conditions. These findings provide optimism for the use of tDCS as delivered in the current study paired with social skills treatment interventions for ASD, particularly for improving skills of emotion verbal fluency.
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2. Guo Z, Xie HQ, Zhang P, Luo Y, Xu T, Liu Y, Fu H, Xu L, Valsami-Jones E, Boksa P, Zhao B. {{Dioxins as potential risk factors for autism spectrum disorder}}. {Environment international}. 2018; 121(Pt 1): 906-15.
Autism spectrum disorder (ASD) has emerged as a major public health concern due to its fast-growing prevalence in recent decades. Environmental factors are thought to contribute substantially to the variance in ASD. Interest in environmental toxins as causes of ASD has arisen due to the high sensitivity of the developing human brain to toxic chemicals, particularly to dioxin and certain dioxin-like compounds (dioxins). As a group of typical persistent organic pollutants, dioxins have been found to exert adverse effects on human brain development. In this paper, we review the evidence for association of exposure to dioxins with neurodevelopmental abnormalities related to ASD based on both human epidemiological and animal studies. It has been documented that exposure to dioxins during critical developmental periods increased risk for ASD. This notion has been demonstrated in different populations exposed to high or background level of dioxins. Furthermore, the effects and mechanisms of action of dioxins relevant to the pathophysiology and pathogenesis of ASD are summarized, describing potential underlying mechanisms linking dioxin exposure with ASD onset. Further studies focusing on effects of prenatal/perinatal exposure to individual dioxin congeners or to mixtures of dioxins on ASD-associated behavioral and neurobiological consequences in animal models, and on the mechanisms of actions of dioxins, are needed in order to better understand how dioxin exposure might contribute to increased risk for ASD.
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3. Keogh C, Pini G, Dyer AH, Bigoni S, DiMarco P, Gemo I, Reilly R, Tropea D. {{Clinical and genetic Rett syndrome variants are defined by stable electrophysiological profiles}}. {BMC pediatrics}. 2018; 18(1): 333.
BACKGROUND: Rett Syndrome (RTT) is a complex neurodevelopmental disorder, frequently associated with epilepsy. Despite increasing recognition of the clinical heterogeneity of RTT and its variants (e.g Classical, Hanefeld and PSV(Preserved Speech Variant)), the link between causative mutations and observed clinical phenotypes remains unclear. Quantitative analysis of electroencephalogram (EEG) recordings may further elucidate important differences between the different clinical and genetic forms of RTT. METHODS: Using a large cohort (n = 42) of RTT patients, we analysed the electrophysiological profiles of RTT variants (genetic and clinical) in addition to epilepsy status (no epilepsy/treatment-responsive epilepsy/treatment-resistant epilepsy). The distribution of spectral power and inter-electrode coherence measures were derived from continuous resting-state EEG recordings. RESULTS: RTT genetic variants (MeCP2/CDLK5) were characterised by significant differences in network architecture on comparing first principal components of inter-electrode coherence across all frequency bands (p < 0.0001). Greater coherence in occipital and temporal pairs were seen in MeCP2 vs CDLK5 variants, the main drivers in between group differences. Similarly, clinical phenotypes (Classical RTT/Hanefeld/PSV) demonstrated significant differences in network architecture (p < 0.0001). Right tempero-parietal connectivity was found to differ between groups (p = 0.04), with greatest coherence in the Classical RTT phenotype. PSV demonstrated a significant difference in left-sided parieto-occipital coherence (p = 0.026). Whilst overall power decreased over time, there were no difference in asymmetry and inter-electrode coherence profiles over time. There was a significant difference in asymmetry in the overall power spectra between epilepsy groups (p = 0.04) in addition to occipital asymmetry across all frequency bands. Significant differences in network architecture were also seen across epilepsy groups (p = 0.044). CONCLUSIONS: Genetic and clinical variants of RTT are characterised by discrete patterns of inter-electrode coherence and network architecture which remain stable over time. Further, hemispheric distribution of spectral power and measures of network dysfunction are associated with epilepsy status and treatment responsiveness. These findings support the role of discrete EEG profiles as non-invasive biomarkers in RTT and its genetic/clinical variants. Lien vers le texte intégral (Open Access ou abonnement)
4. Mohammadian Rad N, van Laarhoven T, Furlanello C, Marchiori E. {{Novelty Detection using Deep Normative Modeling for IMU-Based Abnormal Movement Monitoring in Parkinson’s Disease and Autism Spectrum Disorders}}. {Sensors (Basel, Switzerland)}. 2018; 18(10).
Detecting and monitoring of abnormal movement behaviors in patients with Parkinson’s Disease (PD) and individuals with Autism Spectrum Disorders (ASD) are beneficial for adjusting care and medical treatment in order to improve the patient’s quality of life. Supervised methods commonly used in the literature need annotation of data, which is a time-consuming and costly process. In this paper, we propose deep normative modeling as a probabilistic novelty detection method, in which we model the distribution of normal human movements recorded by wearable sensors and try to detect abnormal movements in patients with PD and ASD in a novelty detection framework. In the proposed deep normative model, a movement disorder behavior is treated as an extreme of the normal range or, equivalently, as a deviation from the normal movements. Our experiments on three benchmark datasets indicate the effectiveness of the proposed method, which outperforms one-class SVM and the reconstruction-based novelty detection approaches. Our contribution opens the door toward modeling normal human movements during daily activities using wearable sensors and eventually real-time abnormal movement detection in neuro-developmental and neuro-degenerative disorders.
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5. Tomczak MT, Wojcikowski M, Listewnik P, Pankiewicz B, Majchrowicz D, Jedrzejewska-Szczerska M. {{Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor(-)A Preliminary Study}}. {Sensors (Basel, Switzerland)}. 2018; 18(10).
The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the sensor, on the body, to gain the most accurate readings of user stress levels, under various conditions. Trial tests were performed on a group of sixteen people to verify the correct functioning of the device. Resistance levels were compared to those from the reference system. The placement of the sensor has also been determined, based on wearer convenience. With the Bluetooth Low Energy block, users can be notified immediately about their abnormal stress levels via a smartphone application. This can help people with ASD, and those who work with them, to facilitate stress control and make necessary adjustments to their work environment.
