scholarly journals Complexity analysis of the brain activity in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) due to cognitive loads/demands induced by Aristotle’s type of syllogism/reasoning. A Power Spectral Density and multiscale entropy (MSE) analysis

Heliyon ◽  
2021 ◽  
pp. e07984
Author(s):  
Anastasia G. Papaioannou ◽  
Eva Kalantzi ◽  
Christos C. Papageorgiou ◽  
Kalliopi Korombili ◽  
Anastasia Βokou ◽  
...  
2021 ◽  
Author(s):  
Azadeh Mozhdehfarahbakhsh ◽  
Amirsaeid Moloodi ◽  
Prasun Chakrabarti ◽  
KS Jagannatha Rao ◽  
Babak Kateb ◽  
...  

Background and Objectives: Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are the two most common neurodevelopmental disorders often with overlapping symptoms. Misdiagnosis of these disorders is the leading cause of a variety of problems including inappropriate interventions and improper treatment outcome. Over the last few years, resting state functional magnetic Resonance imaging (rs-fMRI) has received clinical attention among other beneficial brain scan techniques to extract functional connectivity in the brain. However, extracting useful information by human observation is prone to errors. Material and Methods: The above unmet need prompted us to design the present investigation to construct a convolutional neural network model with 12 layers architecture in rsFMRI data aiming to differentiate the two conditions. The rs-fMRI data was collected from the ADHD-200 and ABIDE to feed into a convolutional neural network. Over the preprocessing phase, we have removed undesirable data and coordinated the remaining to MSDL atlas to recruit 39 regions of the brain. Results: Ultimately, out results obtained a 0.92 accuracy, an AUC of 0.97 and loss of 0.17 in classification and discrimination of ADHD and ASD. Conclusion: Though cross-validity with larger datasets is deemed required, the results obtained from the present investigation suggest that convolutional neural network may serve as a beneficial tool to differentiate ADHD and ASD from relatively small fMRI datasets. This further highlights the potential application of deep neural networks for serving the above purpose.


Author(s):  
Karen Bearss ◽  
Aaron J. Kaat

This chapter will review the available evidence on individuals with co-occurring diagnoses of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). This chapter contends that children diagnosed with both disorders (ASD+ADHD) are a subset of the ASD population that is at risk for delayed recognition of their ASD diagnosis, poor treatment response, and poorer functional outcomes compared to those with ASD without ADHD. Specifically, the chapter highlights the best estimates of the prevalence of the comorbidity, the developmental trajectory of people with co-occurring ASD and ADHD, how ADHD symptoms change across development, overlapping genetic and neurobiological risk factors, psychometrics of ADHD diagnostic instruments in an ASD population, neuropsychological and functional impairments associated with co-occurring ASD and ADHD, and the current state of evidence-based treatment for both ASD and ADHD symptoms. Finally, the chapter discusses fruitful avenues of research for improving understanding of this high-risk comorbidity so that mechanism-to-treatment pathways for ADHD in children with ASD can be better developed.


2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Viktoria Johansson ◽  
Sven Sandin ◽  
Zheng Chang ◽  
Mark J. Taylor ◽  
Paul Lichtenstein ◽  
...  

Abstract Background Clinical studies found that medication for attention-deficit/hyperactivity disorder (ADHD) is effective in coexisting autism spectrum disorder (ASD), but current research is based on small clinical studies mainly performed on children or adolescents. We here use register data to examine if individuals with ADHD and coexisting ASD present differences in the prescribing patterns of ADHD medication when compared to individuals with pure ADHD. Methods Data with information on filled prescriptions and diagnoses was retrieved from the Swedish Prescribed Drug Register and the National Patient Register. We identified 34,374 individuals with pure ADHD and 5012 individuals with ADHD and coexisting ASD, aged between 3 and 80 years. The first treatment episode with ADHD medications (≥ 2 filled prescriptions within 90 days) and daily doses of methylphenidate during a 3-year period was measured. Odds ratios (ORs) were calculated for the likelihood of being prescribed ADHD medication in individuals with and without ASD and Wilcoxon rank-sum test was used to compare group differences in dose per day. Results Individuals with ADHD and coexisting ASD were less likely to start continuous treatment with ADHD medication (ADHD 80.5%; ADHD with ASD 76.2%; OR, 0.80; 95% confidence interval, 0.75-0.86), were less likely to be prescribed methylphenidate, and were more commonly prescribed second line treatments such as dexamphetamine, amphetamine, or modafinil. No group difference was observed for atomoxetine. In adults with ADHD and coexisting ASD, methylphenidate was prescribed in lower daily doses over three years as compared to individuals with pure ADHD. Conclusions The findings indicate that there are differences in the medical treatment of individuals with or without ASD. If these differences are due to different medication responses in ASD or due to other factors such as clinicians’ perceptions of medication effects in patients with ASD, needs to be further studied.


Sign in / Sign up

Export Citation Format

Share Document