Showing 10 results for Autism
Vida Mehdizadehfar, Farnaz Ghassemi, Ali Fallah,
Volume 10, Issue 5 (9-2019)
Abstract
Introduction: Many theories have been proposed about the etiology of autism. One is related to brain connectivity in patients with autism. Several studies have reported brain connectivity changes in autism disease. This study was performed on Electroencephalogram (EEG) studies that evaluated patients with autism, using functional brain connectivity, and compared them with typically-developing individuals.
Methods: Three scientific databases of ScienceDirect, Medline (PubMed), and BioMed Central were systematically searched through their online search engines. Comprehensive Meta-analysis software analyzed the obtained data.
Results: The systematic search led to 10 papers, in which EEG coherence was used to obtain the brain connectivity of people with autism. To determine the effect size, Cohen’s d parameter was used. In the first meta-analysis, the study of the maximum effect size was considered, and all significant effect sizes were evaluated in the second meta-analysis. The effect size was assessed using a random-effects model in both meta-analyses. The results of the first meta-analysis indicated that heterogeneity was not present among the studies (Q=13.345, P>0.1). The evaluation of all effect sizes in the second meta-analysis showed a significant lack of homogeneity among the studies (Q=56.984, P=0.0001).
Conclusion: On the whole, autism was found to be related to neural connectivity, and the present research showed the difference in the EEG coherence of people with autism and healthy people. These conclusions require further studies with more extensive data, considering different brain regions, and novel analysis techniques for assessing brain connectivity.
Raheleh Mollajani, Mohamad Taghi Joghataei, Mehdi Tehrani-Doost,
Volume 10, Issue 5 (9-2019)
Abstract
Introduction: Autism Spectrum Disorder (ASD) is characterized by several impairments in communications and social interactions, as well as restricted interests or stereotyped behaviors. Interventions applied for this disorder are based on multi-modal approaches, including pharmacotherapy. No definitive cure or medication has been introduced so far; therefore, researchers still investigate potential drugs for treating ASD. One of the new medications introduced for this purpose is bumetanide. The present article aimed to review the efficacy of this drug on the core symptoms of ASD and its potential side effects.
Methods: We searched all papers reported on pharmacokinetics, pharmacodynamics, efficacy, and adverse effects of bumetanide on animal models and humans with ASD. The papers were extracted from the main databases of PubMed, Web of Science, and Scopus.
Results: The findings revealed that cortical neurons have high chloride ion (Cl−)i and excitatory actions of gamma-aminobutyric acid in the valproic acid animal model with ASD and mice with fragile X syndrome. Bumetanide, which has been introduced as a diuretic, is also a high-affinity-specific Na+-K+-Cl− cotransporter (NKCC1) antagonist that can reduce Cl− level. The results also indicate that bumetanide can attenuate behavioral features of autism in both animal and human models. Moreover, the studies showed that such medication could activate fusiform face area in individuals with ASD while viewing emotional faces. Also, recent findings suggest that a dose of 1 mg/d of this drug, taken twice daily, might be the best compromise between safety and efficacy.
Conclusion: Recent studies provided some evidence that bumetanide can be a novel pharmacological agent in treating core symptoms of ASD. Future studies are required to confirm the efficacy of this medication in individuals with ASD.
Farnaz Faridi, Afrooz Seyedebrahimi, Reza Khosrowabadi,
Volume 13, Issue 6 (11-2022)
Abstract
Introduction: Autism is a heterogeneous neurodevelopmental disorder associated with social, cognitive and behavioral impairments. These impairments are often reported along with alteration of the brain structure such as abnormal changes in the grey matter (GM) density. However, it is not yet clear whether these changes could be used to differentiate various subtypes of autism spectrum disorder (ASD).
Method: We compared the regional changes of GM density in ASD, Asperger's Syndrome (AS) individuals and a group of healthy controls (HC). In addition to regional changes itself, the amount of GM density changes in one region as compared to other brain regions was also calculated. We hypothesized that this structural covariance network could differentiate the AS individuals from the ASD and HC groups. Therefore, statistical analysis was performed on the MRI data of 70 male subjects including 26 ASD (age=14-50, IQ=92-132), 16 AS (age=7-58, IQ=93-133) and 28 HC (age=9-39, IQ=95-144).
Result: The one-way ANOVA on the GM density of 116 anatomically separated regions showed significant differences among the groups. The pattern of structural covariance network indicated that covariation of GM density between the brain regions is altered in ASD.
Conclusion: This changed structural covariance could be considered as a reason for less efficient segregation and integration of information in the brain that could lead to cognitive dysfunctions in autism. We hope these findings could improve our understanding about the pathobiology of autism and may pave the way towards a more effective intervention paradigm.
Reza Bidaki, Seyed Hossein Hekmati Moghaddam, Maryam Sadeh,
Volume 14, Issue 1 (1-2023)
Abstract
Numerous studies in humans and animals hypothesize that gut microbiota dysbiosis is involved in the development of behavioral and neurological diseases such as depression, autism spectrum disorder, Parkinson disease, multiple sclerosis, stroke and Alzheimer's disease. Some of the most salient works so far regarding the brain-gut axis are mentioned below. The current knowledge on the impact of gut microbiota on nervous system diseases is far from being directly used for pharmacologic or nutritional advice toward restoration of normal bodily functions. It seems that a more comprehensive approach should be followed so that the individual effect of each kind of intervention on the patient’s somatic or psychological status is determined. Future research must address global need for regimens which could re-establish normal composition of gut microorganisms after each neuropsychological disorder.
Asmaa S Mohamed, Hosam M Ahmad, Ahmed A Abdelrahman, Usama F Aly, Khaled A Khaled,
Volume 14, Issue 4 (7-2023)
Abstract
Introduction: In this research, we investigated any possible effect of receiving hyperbaric oxygen therapy (HBOT) or risperidone on the core symptoms of autism in children diagnosed with autism spectrum disorder (ASD).
Methods: This study was a randomized, controlled clinical trial in Minia and Assiut University hospitals in Egypt with three parallel groups. One hundred and eighty children with autism, aged 5–8 years were divided into three equal groups (n=60). Group 1 (G1) received 40 sessions of HBOT within two months, group 2 (G2) received risperidone (dose: 0.25 mg per day in children weighing less than 20 kg and 0.5 mg per day in cases weighing more) for six months, and group 3 (G3) as the control group, received a placebo for six months. The assessment was done using childhood autism rating scale (CARS) and autism treatment evaluation checklist (ATEC) at the beginning of the study (baseline) and after one year.
Results: The mean total CARS and ATEC scores significantly decreased (improved) by varying degrees in the three groups after a year of follow-up compared to the baseline scores, but the best results were found in G1, G2, and G3, respectively.
Conclusion: Using HBOT or risperidone is effective in treating the core symptoms of autism in children diagnosed with autism spectrum disorder, but using HBOT gives better results than risperidone therapy.
Seyed Amir Hossein Batouli, Foroogh Razavi, Minoo Sisakhti, Zeinab Oghabian, Haady Ahmadzade, Mehdi Tehrani Doost,
Volume 14, Issue 5 (9-2023)
Abstract
Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with symptoms appearing from early childhood. Behavioral modifications, special education, and medicines are used to treat ASD; however, the effectiveness of the treatments depends on early diagnosis of the disorder. The primary approach in diagnosing ASD is based on clinical interviews and valid scales. Still, methods based on brain imaging could also be possible diagnostic biomarkers for ASD.
Methods: To identify the amount of information the functional magnetic resonance imaging (fMRI) reveals on ASD, we reviewed 292 task-based fMRI studies on ASD individuals. This study is part of a systematic review with the registration number CRD42017070975.
Results: We observed that face perception, language, attention, and social processing tasks were mainly studied in ASD. In addition, 73 brain regions, nearly 83% of brain grey matter, showed an altered activation between the ASD and normal individuals during these four tasks, either in a lower or a higher activation.
Conclusion: Using imaging methods, such as fMRI, to diagnose and predict ASD is a great objective; research similar to the present study could be the initial step.
Zahra Zolghadr, Seyed Amir Hossein Batouli, Hamid Alavi Majd, Lida Shafaghi, Yadollah Mehrabi,
Volume 15, Issue 3 (5-2024)
Abstract
Introduction: Neurodevelopmental disorders comprise a group of neuropsychiatric conditions. Presently, behavior-based diagnostic approaches are utilized in clinical settings, but the overlapping features among these disorders obscure their recognition and management. Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have common characteristics across various levels, from genes to symptoms. Designing a computational framework based on the neuroimaging findings could provide a discriminative tool for ultimate more efficient treatment. Machine learning approaches, specifically classification methods are among the most applied techniques to reach this goal.
Methods: We applied a novel two-level multi-class data maximum dispersion classifier (DMDC) algorithm to classify the functional neuroimaging data (utilizing datasets: ADHD-200 and autism brain imaging data exchange (ABIDE)) into two categories: Neurodevelopmental disorders (ASD and ADHD) or healthy participants, based on calculated functional connectivity values (statistical temporal correlation).
Results: Our model achieved a total accuracy of 62% for healthy controls. Specifically, it demonstrated an accuracy of 51% for healthy subjects, 61% for autism spectrum disorder, and 84% for ADHD. The support vector machine (SVM) model achieved an accuracy of 46% for both the healthy control and ASD groups, while the ADHD group classification accuracy was estimated to be 84%. These two models showed similar classification indices for the ADHD group. However, the discrimination power was higher in the ASD class.
Conclusion: The method employed in this study demonstrated acceptable performance in classifying disorders and healthy conditions compared to the more commonly used SVM method. Notably, functional connections associated with the cerebellum showed discriminative power.
Fatemeh Abadi, Ali Reza Moradi, Hadi Zarafshan, Mohamad-Reza Mohamadi, Meysam Sadeghi,
Volume 15, Issue 6 (11-2024)
Abstract
Introduction: Interventions using ‘hybrid’ remediation/compensatory cognitive interventions may be beneficial to improving the socio-cognitive functioning of children with autism spectrum disorder (ASD). Previous studies have shown that neurocognitive impairments in executive function (EF) and theory of mind (TOM) are specifically associated with ASD. The primary objective of the study is to determine the impact of the remediation and compensatory cognitive intervention on EFs and TOM abilities. The secondary objective is to evaluate TOM and EF behavioral domains due to the remediation and compensatory cognitive intervention.
Methods: A total of 75 children aged 4 to 7 years diagnosed with high-functioning autism and their parents will be recruited to this double-blind, multicenter, multi-arm randomized controlled trial. The primary outcomes are EFs and TOM as measured by the shape school, shape span test, TOM scale, TOM story books, TOM assessment checklist, and EFs assessment checklist. The secondary outcome is EFs and TOM behavioral domains as measured by the TOM behavior checklist and brief-preschool version at baseline (T0), post-test (T1), 1-month follow-up (T2), and 3-month follow-up (T3). Primary and secondary outcomes will be analyzed using repeated measures, such as an analysis of variance and a mixed model.
Conclusion: This study will assess whether the cognitive intervention program affects not only the neuropsychological functioning of children with ASD but also daily functioning. If the current trial shows that either the remediation or compensatory approaches effectively improve socio-cognitive functioning, the trial would reveal a ‘hybrid’ remediation/compensatory approach.
Raheleh Mollajani, Mohamad Taghi Joghataei, Mehdi Tehrani-Doost, Reza Khosrowabadi,
Volume 16, Issue 1 (1-2025)
Abstract
Introduction: Individuals with autism spectrum disorder (ASD) have impairments in emotion processing, including recognizing facial emotions. There is a significant need for medication to improve core symptoms of ASD. Bumetanide is one of the most recently used drugs in some studies of ASD to address this need. This study aimed to evaluate the effect of bumetanide on the brain response of youth with ASD while they were recognizing facial emotions using the event-related potentials (ERPs).
Methods: Fifteen children with ASD aged between 7 to 16 years were evaluated using the childhood autism rating scale (CARS), schedule for affective disorders and schizophrenia for school-age children-present and lifetime version, social responsiveness scale, Wechsler intelligence scale for children-revised form, and standard blood tests. The electrical brain response was measured while they were doing a facial emotion recognition task (FERT). After 3 months of treatment, they were assessed again regarding core symptoms and ERPs.
Results: The behavioral problems of the participants decreased significantly based on CARS. With regard to behavioral performance on FERT, the accuracy of detecting emotions increased, and reaction time decreased significantly. The amplitude of N170, EPN, and N250 increased, and latency for N170 and N250 decreased significantly in some electrodes. There were no serious side effects.
Conclusion: In this study, bumetanide improved behavioral symptoms and recognition of facial emotions. Also, brain function was improved based on the ERP components. So, bumetanide can be used safely in children and adolescents with ASD to improve the main symptoms of the disorder.
Faezeh Dehghan, Mehdi Alizadeh Zarei, Reza Khosro Abadi, Hashem Farhangdost, Amir Ali Soltani Tehrani, Mohamad Taghi Joghataei,
Volume 16, Issue 2 (3-2025)
Abstract
Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder. The pattern of eye movements during reading can significantly impact reading quality. This study aimed to examine the eye movement patterns, which are essential for reading, in children with ASD compared to their neurotypical peers.
Methods: This study focused on two crucial indicators influencing reading: Eye fixation time and saccade movement. A comparison of parameters of saccade movements and eye fixation in a sentence reading task was done between two groups using an eye tracker device. Autistic children (15 children, mean age: 102.33 months) and their neurotypical peers (17 children, mean age: 101.69 months) participated in this study.
Results: Compared to their neurotypical peers, children with ASD had lower amplitude while reading sentences (P=0.02). These children used more fixations to read the words in the sentence (P=0.02). Comparing the total time spent reading a sentence between the two groups shows that autistic children need more time to read a sentence (P=0.02).
Conclusion: These results suggest that low-level sensorimotor processes in generating accurate eye movements, such as the dorsal visual pathway and cerebellum, can significantly impact the reading quality of children with ASD.
