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RISS 인기검색어
- 검색키워드
- 저자 : Ali Mohammadi Nasrabadi (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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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.
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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.
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Amin Piri,유기현,Milad Massoudifarid,Ali Mohammadi Nasrabadi,황정호 한국대기환경학회 2021 한국대기환경학회 학술대회논문집 Vol.2021 No.10
Fossil fuel-based powerplants are vastly used for electricity generation. However, through fossil fuel combustion, high concentration of harmful gases such as Nitrogen oxides (NOx) and sulfur oxides (SOx) are produced and released to the environment. Several techniques are available to control NOx emissions: selective catalytic reduction, selective non-catalytic reduction, adsorption, scrubbing, flue-gas desulfurization, wet scrubber, electrostatic precipitation and biological methods. Although, few of these methods have shown great potential for NOx removal, there is still the need for more effective methodologies with high reduction rates and low costs. Ascorbic acid (AA) is a powerful antioxidant that acts as a scavenger for ROS and RNS. Thus, It can reduce NOx concentrations in solutions. On the other hand, NOx such as NO and NO₂ can react with bacterial cell components. Bacteria suspensions can be used to react with NOx and therefore, reduce their concentration in solutions. In this study, for the first time, an effective and low-cost methodology is introduced for removal of NOx emission from air via ascorbic acid based bio-reactor for a fossil fuel powerplant. Various liquid solutions and bacterial suspensions were tested to chose the optimal conditions and the results indicate that our methodology is effective in removing NOx emissions from air.
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