1. Heunis T, Aldrich C, Peters JM, Jeste SS, Sahin M, Scheffer C, de Vries PJ. {{Recurrence quantification analysis of resting state EEG signals in autism spectrum disorder – a systematic methodological exploration of technical and demographic confounders in the search for biomarkers}}. {BMC medicine}. 2018; 16(1): 101.
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a worldwide prevalence of 1-2%. In low-resource environments, in particular, early identification and diagnosis is a significant challenge. Therefore, there is a great demand for ‘language-free, culturally fair’ low-cost screening tools for ASD that do not require highly trained professionals. Electroencephalography (EEG) has seen growing interest as an investigational tool for biomarker development in ASD and neurodevelopmental disorders. One of the key challenges is the identification of appropriate multivariate, next-generation analytical methodologies that can characterise the complex, nonlinear dynamics of neural networks in the brain, mindful of technical and demographic confounders that may influence biomarker findings. The aim of this study was to evaluate the robustness of recurrence quantification analysis (RQA) as a potential biomarker for ASD using a systematic methodological exploration of a range of potential technical and demographic confounders. METHODS: RQA feature extraction was performed on continuous 5-second segments of resting state EEG (rsEEG) data and linear and nonlinear classifiers were tested. Data analysis progressed from a full sample of 16 ASD and 46 typically developing (TD) individuals (age 0-18 years, 4802 EEG segments), to a subsample of 16 ASD and 19 TD children (age 0-6 years, 1874 segments), to an age-matched sample of 7 ASD and 7 TD children (age 2-6 years, 666 segments) to prevent sample bias and to avoid misinterpretation of the classification results attributable to technical and demographic confounders. A clinical scenario of diagnosing an unseen subject was simulated using a leave-one-subject-out classification approach. RESULTS: In the age-matched sample, leave-one-subject-out classification with a nonlinear support vector machine classifier showed 92.9% accuracy, 100% sensitivity and 85.7% specificity in differentiating ASD from TD. Age, sex, intellectual ability and the number of training and test segments per group were identified as possible demographic and technical confounders. Consistent repeatability, i.e. the correct identification of all segments per subject, was found to be a challenge. CONCLUSIONS: RQA of rsEEG was an accurate classifier of ASD in an age-matched sample, suggesting the potential of this approach for global screening in ASD. However, this study also showed experimentally how a range of technical challenges and demographic confounders can skew results, and highlights the importance of probing for these in future studies. We recommend validation of this methodology in a large and well-matched sample of infants and children, preferably in a low- and middle-income setting.
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2. Khalil R, Tindle R, Boraud T, Moustafa AA, Karim AA. {{Social decision making in autism: On the impact of mirror neurons, motor control, and imitative behaviors}}. {CNS neuroscience & therapeutics}. 2018; 24(8): 669-76.
The Mirror Neuron System (MNS) plays a crucial role in action perception and imitative behavior, which is suggested to be impaired in Autism Spectrum Disorders (ASDs). In this review, we discuss the plausibility and empirical evidence of a neural interaction between the MNS, action perception, empathy, imitative behavior, and their impact on social decision making in ASDs. To date, there is no consensus regarding a particular theory in ASDs and its underlying mechanisms. Some theories have completely focused on social difficulties, others have emphasized sensory aspects. Based on the current studies, we suggest a multilayer neural network model including the MNS on a first layer and transforming this information to a higher layer network responsible for reasoning. Future studies with ASD participants combining behavioral tasks with neuroimaging methods and transcranial brain stimulation as well as computational modeling can help validate and complement this suggested model. Moreover, we propose applying the behavioral paradigms, and the neurophysiological markers mentioned in this review article for evaluating psychiatric treatment approaches in ASDs. The investigation of modulating effects of different treatment approaches on the neurophysiological markers of the MNS can help find specific subgroups of ASDs patients and support tailored psychiatric interventions.
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3. Lammert CR, Frost EL, Bolte AC, Paysour MJ, Shaw ME, Bellinger CE, Weigel TK, Zunder ER, Lukens JR. {{Cutting Edge: Critical Roles for Microbiota-Mediated Regulation of the Immune System in a Prenatal Immune Activation Model of Autism}}. {Journal of immunology (Baltimore, Md : 1950)}. 2018; 201(3): 845-50.
Recent studies suggest that autism is often associated with dysregulated immune responses and altered microbiota composition. This has led to growing speculation about potential roles for hyperactive immune responses and the microbiome in autism. Yet how microbiome-immune cross-talk contributes to neurodevelopmental disorders currently remains poorly understood. In this study, we report critical roles for prenatal microbiota composition in the development of behavioral abnormalities in a murine maternal immune activation (MIA) model of autism that is driven by the viral mimetic polyinosinic-polycytidylic acid. We show that preconception microbiota transplantation can transfer susceptibility to MIA-associated neurodevelopmental disease and that this is associated with modulation of the maternal immune response. Furthermore, we find that ablation of IL-17a signaling provides protection against the development of neurodevelopmental abnormalities in MIA offspring. Our findings suggest that microbiota landscape can influence MIA-induced neurodevelopmental disease pathogenesis and that this occurs as a result of microflora-associated calibration of gestational IL-17a responses.
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4. Melancia F, Schiavi S, Servadio M, Cartocci V, Campolongo P, Palmery M, Pallottini V, Trezza V. {{Sex specific autistic endophenotypes induced by prenatal exposure to valproic acid involve anandamide signaling}}. {British journal of pharmacology}. 2018.
BACKGROUND AND PURPOSE: Autism spectrum disorder (ASD) is more commonly diagnosed in males than in females. Prenatal exposure to the antiepileptic drug valproic acid (VPA) is an environmental risk factor of ASD. Male rats prenatally exposed to VPA show socio-emotional autistic-like dysfunctions that have been related with changes in the activity of the endocannabinoid anandamide. Our aim was to investigate whether prenatal VPA induces sex specific autistic endophenotypes involving anandamide signaling. EXPERIMENTAL APPROACH: We studied sex-specific differences in the ASD-like socio-emotional, cognitive and repetitive symptoms displayed in the course of development by rats prenatally exposed to VPA, and investigated the role of anandamide in the autistic-like symptoms displayed by VPA-exposed rats of both sexes. KEY RESULTS: Female rats were less vulnerable to the deleterious effects of prenatal VPA exposure on social communication, emotional reactivity and cognitive performance than male rats. Conversely, similarly to what happens in male rats, prenatal VPA exposure induced selective deficits in social play behavior and stereotypies in the female rat offspring. At the neurochemical level, prenatal VPA exposure altered the phosphorylation of CB1 cannabinoid receptors in a sex-, age- and tissue-specific manner. Enhancing anandamide signaling through inhibition of its degradation reversed the behavioral deficits displayed by VPA-exposed animals of both sexes. CONCLUSION AND IMPLICATION: These findings highlight sexually-dimorphic consequences of prenatal VPA exposure that may be related to a sex-specific impact of VPA on endocannabinoid neurotransmission in the course of development, and introduce a new therapeutic target for reversing autistic-like symptoms in both sexes.
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5. Mensi MM, Gasparini L, Chiappedi M, Guerini FR, Orlandi M, Rogantini C, Balottin U. {{Empathy and behavior in children affected by Autism Spectrum Disorders}}. {Minerva pediatrica}. 2018.
BACKGROUND: Many studies have already shown that individuals suffering from Autism Spectrum Disorders (ASD) present low levels of empathy: in fact, reduced emotional reciprocity is considered a clinically significant indicator of autistic functioning. We decided to investigate the role of empathy in determining pathological behaviors in children affected by ASD considering parents’ point of view and to evaluate the presence of differences between mothers and fathers’ perception of their child’s empathy and behaviors. METHODS: We compared empathy levels in a sample of 58 patients with ASD as reported by a parent-filled questionnaire with the results of a global evaluation conducted by means of play observations, clinician-rated scales, a semi-structured interview with both caregivers and parent-filled questionnaires. RESULTS: The majority of ASD patients have low levels of empathy according to both parents’ points of view; noteworthy, mothers and fathers are highly concordant in this respect. Children’s levels of empathy negatively correlate with many behavioral problems, both internalizing and externalizing. Furthermore, we found that mothers tend to perceive more internalizing problems, while fathers are more willing to notice externalizing ones. CONCLUSIONS: Involving both caregivers in children’s diagnostic assessment could deepen patient’s evaluation and finally the therapeutic results. Mothers and fathers seem to be highly consistent in describing the psychological characteristics of their child, but not in respect to symptoms.
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6. Poole D, Gowen E, Warren PA, Poliakoff E. {{Visual-tactile selective attention in autism spectrum condition: An increased influence of visual distractors}}. {Journal of experimental psychology General}. 2018.
We have previously observed that participants with autism spectrum condition (ASC) are more influenced by visual distractors during a tactile task compared with controls (Poole, Gowen, Warren, & Poliakoff, 2015). This finding suggests that changes in multisensory processing could underpin differences in sensory reactivity in ASC. Here we explore the cognitive mechanisms underlying this effect. Adults with ASC (n = 22) and matched neurotypical (NT) controls (n = 22) completed 3 tasks involving similar stimuli. In Experiment 1, we again showed that when participants with ASC were performing a tactile task they were distracted more by visual stimuli compared with NTs. In Experiment 2, however, no differences between the groups were observed on an alternative visual-tactile task (temporal order judgment) requiring attention to both the stimuli. That is, ASC performance was typical when the task did not require the visual stimuli to be suppressed. Furthermore, in Experiment 3 the effects of visual distractors were comparable between the groups when the tactile target was replaced with a visual target. When comparing performance across Experiments 1 and 3, NT participants were better able to suppress visual distractors when the target was tactile than when the target was visual (Experiment 1 vs. 3), but this crossmodal benefit was not observed in participants with ASC. The effects of visual distractors were comparable regardless of the target modality suggesting that the efficacy of visual-tactile selective attention may be reduced in ASC. (PsycINFO Database Record
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7. Shephard E, Bedford R, Milosavljevic B, Gliga T, Jones EJH, Pickles A, Johnson MH, Charman T. {{Early developmental pathways to childhood symptoms of attention-deficit hyperactivity disorder, anxiety and autism spectrum disorder}}. {J Child Psychol Psychiatry}. 2018.
BACKGROUND: Children with autism spectrum disorder (ASD) often have co-occurring symptoms of attention-deficit/hyperactivity disorder (ADHD) and/or anxiety. It is unclear whether these disorders arise from shared or distinct developmental pathways. We explored this question by testing the specificity of early-life (infant and toddler) predictors of mid-childhood ADHD and anxiety symptoms compared to ASD symptoms. METHODS: Infants (n = 104) at high and low familial risk for ASD took part in research assessments at 7, 14, 24 and 38 months, and 7 years of age. Symptoms of ASD, ADHD and anxiety were measured by parent report at age 7. Activity levels and inhibitory control, also measured by parent report, in infancy and toddlerhood were used as early-life predictors of ADHD symptoms. Fearfulness and shyness measured in infancy and toddlerhood were used as early-life predictors of anxiety symptoms. Correlations and path analysis models tested associations between early-life predictors and mid-childhood ADHD and anxiety symptoms compared to mid-childhood ASD symptoms, and the influence of controlling for ASD symptoms on those associations. RESULTS: Increased activity levels and poor inhibitory control were correlated with ADHD symptoms and not ASD or anxiety; these associations were unchanged in path models controlling for risk-group and ASD symptoms. Increased fearfulness and shyness were correlated with anxiety symptoms, but also ASD symptoms. When controlling for risk-group in path analysis, the association between shyness and anxiety became nonsignificant, and when further controlling for ASD symptoms the association between fearfulness and anxiety became marginal. CONCLUSIONS: The specificity of early-life predictors to ADHD symptoms suggests early developmental pathways to ADHD might be distinct from ASD. The overlap in early-life predictors of anxiety and ASD suggests that these disorders are difficult to differentiate early in life, which could reflect the presence of common developmental pathways or convergence in early behavioural manifestations of these disorders.