Effects of Non-invasive Neurostimulation on Autism Spectrum Disorder: A Systematic Review

Ali Khaleghi,Hadi Zarafshan,Safa Rafieivand,Mohammad Reza Mohammadi 대한정신약물학회 2020 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.18 No.4

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by major impairments in social communication, stereotyped and ritualistic behaviors and deficits in sensory reactivity. Recently, noninvasive brain stimulation (NIBS) methods, namely transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), have been examined as possible new therapeutic options for modifying the pathological neuroplasticity involved in neuropsychiatric disorders including ASD. Therefore, we conducted a systematic review on the therapeutic uses of tDCS and repetitive TMS (rTMS) in ASD patients. A systematic search was performed on Scopus, Web of Science, PubMed, Cochrane and Embase. Original articles reporting the use of tDCS or rTMS to treat ASD were screened and studied by two researchers independently based on PRISMA guidelines. We found 32 eligible studies including 8 tDCS reports, 23 rTMS reports and one report with both tDCS and rTMS. These studies comprised 6 case-reports, 9 non-controlled trials and 17 controlled trials which assessed NIBS effects on the three cognitive, behavioral and biological dimensions in ASD. Existing evidence demonstrates that NIBS methods could be helpful for treating some dimensions of ASD such as repetitive behavior, sociability or some aspects of executive and cognitive functions. However, such evidence should be regarded with care because of the quality of original researches and serious publication bias as well as the heterogeneity of data. Further randomized, double-blind, sham-controlled trials with appropriate follow-up periods should be designed to assess the efficacy of NIBS methods for ASD treatment.

Single-Phase Fault Location in Four-Circuit Transmission Lines Based on Wavelet Analysis Using ANFIS

Ali Khaleghi,Mahmoud Oukati Sadegh 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.4

This paper presents an effi cient and eff ective method to determine the location of the single phase to ground fault in fourcircuit transmission lines. In the proposed method, wavelet analysis based on advanced signal processing techniques are used to extract important features and record the dynamic characteristics of the fault signal using current sampled data of one side of the line. In this regard, the ANFIS network is used to fi nd the relationship between the obtained characteristics from wavelet signal analysis of the fault signal and the changes in diff erent fault conditions. In proposed method, there is no need to know the type of the fault or line information. Also, determination of faulty circuit and the use of intelligent methods to reduce computations are among the advantages of the proposed method. Studies and simulations have been implemented on a four-circuit transmission line of 500 kV and 200 km in PSCAD software. The results of wavelet analysis have been applied as an input of ANFIS network in MATLAB software. The results of the simulations are based on the implementation of different fault conditions, including the faulty circuit, fault location, fault inception, and fault resistance. These results indicate the high accuracy of the proposed method.

Computational Neuroscience Approach to Psychiatry: A Review on Theory-driven Approaches

Ali Khaleghi,Mohammad Reza Mohammadi,Kian Shahi,Ali Motie Nasrabadi 대한정신약물학회 2022 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.20 No.1

Translating progress in neuroscience into clinical benefits for patients with psychiatric disorders is challenging because it involves the brain as the most complex organ and its interaction with a complex environment and condition. Dealing with such complexity requires powerful techniques. Computational neuroscience approach to psychiatry integrates multiple levels and types of simulation, analysis and computation according to the different types of computational models to enhance comprehending, prediction and treatment of psychiatric disorder. This approach comprises two approaches: theory-driven and data-driven. In this review, we focus on recent advances in theory-driven approaches that mathematically and mechanistically examine the relationships between disorder-related changes and behavior at different level of brain organization. We discuss recent progresses in computational neuroscience models that relate to psychiatry and show how principles of neural computational modeling can be employed to explain psychopathology.

Neuro-cognitive Ramifications of Fasting and Feeding in Obese and Non-obese Cases

Seyed-Ali Mostafavi,Ali Khaleghi,Safa Rafieivand,Seyyed Salman Alavi,Mohammad Reza Mohammadi 대한정신약물학회 2018 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.16 No.4

Preliminary studies have claimed that short term fasting would negatively affect school performance and cognition. In contrast some other studies have reported not important decline in cognition and executive function as a result of fasting. Also limited attention was generally devoted to dietetic regimens, nutritional status and body weight. Yet neuroscience and neuro-cognitive aspects of acute hunger on the electroencephalogram and differences between obese and non-obese cases is not well understood. Hence, we decided to design and perform a case study in a more controlled situation similar to reality. Therefore, we performed several examinations including subjective tests (for eating status) and objective tests (cognitive tests such as Stroop effect and Sternberg search and electroencephalogram measures such as steady-state visual evoked potential and auditory steady-state responses) for an obese and a non-obese academic case before and after a simple breakfast. The results showed that the breakfast effects on the neuro-cognitive functions depend on either obesity status, nutritional status of the case or the type of cognitive task (visual or auditory). This paper would open a new insight to answer some important questions about the neuro-cognitive implications of fasting and feeding in obese and non-obese human cases.

Numerical analysis of the impact of gravity on the internal flow of a rotary atomizer

Ali Charanandeh,Milad Khaleghi Kasbi,Jeekeun Lee 한국전산유체공학회 2022 한국전산유체공학회 학술대회논문집 Vol.2022 No.10

Coanda flow and the influence of design parameters on the swirling flow structure in an airblast nozzle

Milad Khaleghi Kasbi,Ali Charanandeh,Reza Alidoost Dafsari,Seunghwa Yu,Yong Choi,Jeekeun Lee 한국전산유체공학회 2022 한국전산유체공학회 학술대회논문집 Vol.2022 No.10

EEG Classification of ADHD and Normal Children Using Non-linear Features and Neural Network

Mohammad Reza Mohammadi,Ali Khaleghi,Ali Moti Nasrabadi,Safa Rafieivand,Moslem Begol,Hadi Zarafshan 대한의용생체공학회 2016 Biomedical Engineering Letters (BMEL) Vol.6 No.2

Purpose Attention-Deficit Hyperactivity Disorder (ADHD)is a neuro-developmental disorder that is characterized byhyperactivity, inattention and abrupt behaviors. This studyproposes an approach for distinguishing ADHD childrenfrom normal children using their EEG signals when performinga cognitive task. Methods In this study, 30 children with ADHD and 30 agematchedhealthy children without neurological disordersunderwent electroencephalography (EEG) when performinga task to stimulate their attention. Fractal dimension (FD),approximate entropy and lyapunov exponent were extractedfrom EEG signals as non-linear features. In order to improvethe classification results, double input symmetrical relevance(DISR) and minimum Redundancy Maximum Relevance(mRMR) methods were used to select the best features asinputs to multi-layer perceptron (MLP) neural network. Results As expected, children with ADHD had more delaysand were less accurate in doing the cognitive task. Also, theextracted non-linear features revealed that non-linear indiceswere greater in different regions of the brain of ADHDchildren compared to healthy children. This could indicate amore chaotic behavior of ADHD children while performinga cognitive task. Finally, the accuracy of 92.28% and 93.65%were achieved using mRMR method and DISR methodusing MLP, respectively. Conclusions The results of this study demonstrate the abilityof the non-linear features to distinguish ADHD children fromhealthy children.

Transsexualism: A Different Viewpoint to Brain Changes

Mohammad Reza Mohammadi,Ali Khaleghi 대한정신약물학회 2018 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.16 No.2

Transsexualism refers to a condition or belief which results in gender dysphoria in individuals and makes them insist that their biological gender is different from their psychological and experienced gender. Although the etiology of gender dysphoria (or transsexualism) is still unknown, different neuroimaging studies show that structural and functional changes of the brain result from this sexual incongruence. The question here is whether these reported changes form part of the etiology of transsexualism or themselves result from transsexualism culture, behaviors and lifestyle. Responding to this question can be more precise by consideration of cultural neuroscience concepts, particularly the culture–behavior– brain (CBB) loop model and the interactions between behavior, culture and brain. In this article, we first review the studies on the brain of transgender people and then we will discuss the validity of this claim based on the CBB loop model. In summary, transgender individuals experience change in lifestyle, context of beliefs and concepts and, as a result, their culture and behaviors. Given the close relationship and interaction between culture, behavior and brain, the individual’s brain adapts itself to the new condition (culture) and concepts and starts to alter its function and structure.