List of Publications
There are numbers of autism related research can be found in Malaysia that generally focus on the ASD, learning disorder, communication aids, therapy and many more. The list of publications is provided below:
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2019 |
Mohamad, F H; Has, A T C The α5-Containing GABA A Receptors—a Brief Summary Journal Article Journal of Molecular Neuroscience, 67 (2), pp. 343-351, 2019, ISSN: 08958696, (cited By 1). Abstract | Links | BibTeX | Tags: 4 Aminobutyric Acid, 4 Aminobutyric Acid A Receptor, Alpha5 Containing 4 Aminobutyric Acid A Receptor, Animals, Autism, Brain, Cognitive Defect, Cognitive Dysfunction, Drug Effect, GABA Agents, GABA-A, GABAergic Receptor Affecting Agent, Genetics, Human, Metabolism, Nonhuman, Protein Subunit, Protein Subunits, Receptors, Review, Schizophrenia, Unclassified Drug @article{Mohamad2019343, title = {The α5-Containing GABA A Receptors—a Brief Summary}, author = {F H Mohamad and A T C Has}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059596842&doi=10.1007%2fs12031-018-1246-4&partnerID=40&md5=7b2ba0dc86c6c3f890f226cad8195ee5}, doi = {10.1007/s12031-018-1246-4}, issn = {08958696}, year = {2019}, date = {2019-01-01}, journal = {Journal of Molecular Neuroscience}, volume = {67}, number = {2}, pages = {343-351}, publisher = {Springer New York LLC}, abstract = {GABA A receptors are the major inhibitory neurotransmitter receptor in the human brain. The receptors are assembled from combination of protein subunits in pentameric complex which may consist of α1–6, β1–3, γ1–3, ρ1–3, δ, ε, θ, or π subunits. There are a theoretical > 150,000 possible assemblies and arrangements of GABA A subunits, although only a few combinations have been found in human with the most dominant consists of 2α1, 2β2, and 1γ2 in a counterclockwise arrangement as seen from the synaptic cleft. The receptors also possess binding sites for various unrelated substances including benzodiazepines, barbiturates, and anesthetics. The α5-containing GABA A Rs only make up ≤ 5% of the entire receptor population, but up to 25% of the receptor subtype is located in the crucial learning and memory-associated area of the brain—the hippocampus, which has ignited myriads of hypotheses and theories in regard to its role. As well as exhibiting synaptic phasic inhibition, the α5-containing receptors are also extrasynaptic and mediate tonic inhibition with continuously occurring smaller amplitude. Studies on negative-allosteric modulators for reducing this tonic inhibition have been shown to enhance learning and memory in neurological disorders such as schizophrenia, Down syndrome, and autism with a possible alternative benzodiazepine binding site. Therefore, a few α5 subunit-specific compounds have been developed to address these pharmacological needs. With its small population, the α5-containing receptors could be the key and also the answer for many untreated cognitive dysfunctions and disorders. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.}, note = {cited By 1}, keywords = {4 Aminobutyric Acid, 4 Aminobutyric Acid A Receptor, Alpha5 Containing 4 Aminobutyric Acid A Receptor, Animals, Autism, Brain, Cognitive Defect, Cognitive Dysfunction, Drug Effect, GABA Agents, GABA-A, GABAergic Receptor Affecting Agent, Genetics, Human, Metabolism, Nonhuman, Protein Subunit, Protein Subunits, Receptors, Review, Schizophrenia, Unclassified Drug}, pubstate = {published}, tppubtype = {article} } GABA A receptors are the major inhibitory neurotransmitter receptor in the human brain. The receptors are assembled from combination of protein subunits in pentameric complex which may consist of α1–6, β1–3, γ1–3, ρ1–3, δ, ε, θ, or π subunits. There are a theoretical > 150,000 possible assemblies and arrangements of GABA A subunits, although only a few combinations have been found in human with the most dominant consists of 2α1, 2β2, and 1γ2 in a counterclockwise arrangement as seen from the synaptic cleft. The receptors also possess binding sites for various unrelated substances including benzodiazepines, barbiturates, and anesthetics. The α5-containing GABA A Rs only make up ≤ 5% of the entire receptor population, but up to 25% of the receptor subtype is located in the crucial learning and memory-associated area of the brain—the hippocampus, which has ignited myriads of hypotheses and theories in regard to its role. As well as exhibiting synaptic phasic inhibition, the α5-containing receptors are also extrasynaptic and mediate tonic inhibition with continuously occurring smaller amplitude. Studies on negative-allosteric modulators for reducing this tonic inhibition have been shown to enhance learning and memory in neurological disorders such as schizophrenia, Down syndrome, and autism with a possible alternative benzodiazepine binding site. Therefore, a few α5 subunit-specific compounds have been developed to address these pharmacological needs. With its small population, the α5-containing receptors could be the key and also the answer for many untreated cognitive dysfunctions and disorders. © 2019, Springer Science+Business Media, LLC, part of Springer Nature. |
2018 |
Tsuchida, N; Hamada, K; Shiina, M; Kato, M; Kobayashi, Y; Tohyama, J; Kimura, K; Hoshino, K; Ganesan, V; Teik, K W; Nakashima, M; Mitsuhashi, S; Mizuguchi, T; Takata, A; Miyake, N; Saitsu, H; Ogata, K; Miyatake, S; Matsumoto, N GRIN2D variants in three cases of developmental and epileptic encephalopathy Journal Article Clinical Genetics, 94 (6), pp. 538-547, 2018, ISSN: 00099163, (cited By 4). Abstract | Links | BibTeX | Tags: Adolescent, Allele, Amino Acid Sequence, Amino Acid Substitution, Amino Terminal Sequence, Anemia, Antibiotic Agent, Antibiotic Therapy, Article, Atonic Seizure, Attention Deficit Disorder, Autism, Binding Affinity, Brain, Brain Atrophy, Carbamazepine, Case Report, Channel Gating, Chemistry, Children, Clinical Article, Clinical Feature, Clobazam, Clonazepam, Conformational Transition, Continuous Infusion, Contracture, Crystal Structure, Cysteine Ethyl Ester Tc 99m, Developmental Delay, Developmental Disorders, Electroencephalogram, Electroencephalography, Epilepsy, Epileptic Discharge, Ethosuximide, Eye Tracking, Febrile Convulsion, Female, Frontal Lobe Epilepsy, Gene, Gene Frequency, Genetic Variation, Genetics, Genotype, GRIN2D Protein, Heterozygosity, Home Oxygen Therapy, Human, Human Cell, Hydrogen Bond, Intellectual Impairment, Intelligence Quotient, Intractable Epilepsy, Ketamine, Lacosamide, Lamotrigine, Lennox Gastaut Syndrome, Levetiracetam, Magnetoencephalography, Male, Maternal Hypertension, Melatonin, Migraine, Missense Mutation, Molecular Dynamics, Molecular Dynamics Simulation, Mutation, Myoclonus Seizure, N Methyl Dextro Aspartic Acid Receptor, N Methyl Dextro Aspartic Acid Receptor 2D, N-Methyl-D-Aspartate, Neonatal Pneumonia, Neonatal Respiratory Distress Syndrome, Neuroimaging, Nuclear Magnetic Resonance Imaging, Phenobarbital, Premature Labor, Preschool, Preschool Child, Priority Journal, Protein Conformation, Proximal Interphalangeal Joint, Pyridoxine, Receptors, Respiratory Arrest, Sanger Sequencing, School Child, Single Photon Emission Computed Tomography, Sleep Disordered Breathing, Static Electricity, Stridor, Structure-Activity Relationship, Subglottic Stenosis, Superior Temporal Gyrus, Supramarginal Gyrus, Thiopental, Tonic Seizure, Valproic Acid, Wakefulness, Wechsler Intelligence Scale for Children, Whole Exome Sequencing @article{Tsuchida2018538, title = {GRIN2D variants in three cases of developmental and epileptic encephalopathy}, author = {N Tsuchida and K Hamada and M Shiina and M Kato and Y Kobayashi and J Tohyama and K Kimura and K Hoshino and V Ganesan and K W Teik and M Nakashima and S Mitsuhashi and T Mizuguchi and A Takata and N Miyake and H Saitsu and K Ogata and S Miyatake and N Matsumoto}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056487337&doi=10.1111%2fcge.13454&partnerID=40&md5=f0d32670db57261820bc244943cffd62}, doi = {10.1111/cge.13454}, issn = {00099163}, year = {2018}, date = {2018-01-01}, journal = {Clinical Genetics}, volume = {94}, number = {6}, pages = {538-547}, publisher = {Blackwell Publishing Ltd}, abstract = {N-methyl-d-aspartate (NMDA) receptors are glutamate-activated ion channels that are widely distributed in the central nervous system and essential for brain development and function. Dysfunction of NMDA receptors has been associated with various neurodevelopmental disorders. Recently, a de novo recurrent GRIN2D missense variant was found in two unrelated patients with developmental and epileptic encephalopathy. In this study, we identified by whole exome sequencing novel heterozygous GRIN2D missense variants in three unrelated patients with severe developmental delay and intractable epilepsy. All altered residues were highly conserved across vertebrates and among the four GluN2 subunits. Structural consideration indicated that all three variants are probably to impair GluN2D function, either by affecting intersubunit interaction or altering channel gating activity. We assessed the clinical features of our three cases and compared them to those of the two previously reported GRIN2D variant cases, and found that they all show similar clinical features. This study provides further evidence of GRIN2D variants being causal for epilepsy. Genetic diagnosis for GluN2-related disorders may be clinically useful when considering drug therapy targeting NMDA receptors. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd}, note = {cited By 4}, keywords = {Adolescent, Allele, Amino Acid Sequence, Amino Acid Substitution, Amino Terminal Sequence, Anemia, Antibiotic Agent, Antibiotic Therapy, Article, Atonic Seizure, Attention Deficit Disorder, Autism, Binding Affinity, Brain, Brain Atrophy, Carbamazepine, Case Report, Channel Gating, Chemistry, Children, Clinical Article, Clinical Feature, Clobazam, Clonazepam, Conformational Transition, Continuous Infusion, Contracture, Crystal Structure, Cysteine Ethyl Ester Tc 99m, Developmental Delay, Developmental Disorders, Electroencephalogram, Electroencephalography, Epilepsy, Epileptic Discharge, Ethosuximide, Eye Tracking, Febrile Convulsion, Female, Frontal Lobe Epilepsy, Gene, Gene Frequency, Genetic Variation, Genetics, Genotype, GRIN2D Protein, Heterozygosity, Home Oxygen Therapy, Human, Human Cell, Hydrogen Bond, Intellectual Impairment, Intelligence Quotient, Intractable Epilepsy, Ketamine, Lacosamide, Lamotrigine, Lennox Gastaut Syndrome, Levetiracetam, Magnetoencephalography, Male, Maternal Hypertension, Melatonin, Migraine, Missense Mutation, Molecular Dynamics, Molecular Dynamics Simulation, Mutation, Myoclonus Seizure, N Methyl Dextro Aspartic Acid Receptor, N Methyl Dextro Aspartic Acid Receptor 2D, N-Methyl-D-Aspartate, Neonatal Pneumonia, Neonatal Respiratory Distress Syndrome, Neuroimaging, Nuclear Magnetic Resonance Imaging, Phenobarbital, Premature Labor, Preschool, Preschool Child, Priority Journal, Protein Conformation, Proximal Interphalangeal Joint, Pyridoxine, Receptors, Respiratory Arrest, Sanger Sequencing, School Child, Single Photon Emission Computed Tomography, Sleep Disordered Breathing, Static Electricity, Stridor, Structure-Activity Relationship, Subglottic Stenosis, Superior Temporal Gyrus, Supramarginal Gyrus, Thiopental, Tonic Seizure, Valproic Acid, Wakefulness, Wechsler Intelligence Scale for Children, Whole Exome Sequencing}, pubstate = {published}, tppubtype = {article} } N-methyl-d-aspartate (NMDA) receptors are glutamate-activated ion channels that are widely distributed in the central nervous system and essential for brain development and function. Dysfunction of NMDA receptors has been associated with various neurodevelopmental disorders. Recently, a de novo recurrent GRIN2D missense variant was found in two unrelated patients with developmental and epileptic encephalopathy. In this study, we identified by whole exome sequencing novel heterozygous GRIN2D missense variants in three unrelated patients with severe developmental delay and intractable epilepsy. All altered residues were highly conserved across vertebrates and among the four GluN2 subunits. Structural consideration indicated that all three variants are probably to impair GluN2D function, either by affecting intersubunit interaction or altering channel gating activity. We assessed the clinical features of our three cases and compared them to those of the two previously reported GRIN2D variant cases, and found that they all show similar clinical features. This study provides further evidence of GRIN2D variants being causal for epilepsy. Genetic diagnosis for GluN2-related disorders may be clinically useful when considering drug therapy targeting NMDA receptors. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd |
Sudirman, R; Hussin, S S; Airij, A G; Hai, C Z Profile indicator for autistic children using EEG biosignal potential of sensory tasks Conference Institute of Electrical and Electronics Engineers Inc., 2018, ISBN: 9781538612774, (cited By 0). Abstract | Links | BibTeX | Tags: Autistic Children, Biomedical Signal Processing, Brain, Children with Autism, Electroencephalography, Electrophysiology, Entropy Approximations, Independent Component Analysis, MATLAB, Neural Networks, Neurological Problems, Sensory Analysis, Sensory Profiles, Sensory Stimulation, Wavelet Packet Transforms @conference{Sudirman2018136, title = {Profile indicator for autistic children using EEG biosignal potential of sensory tasks}, author = {R Sudirman and S S Hussin and A G Airij and C Z Hai}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058032461&doi=10.1109%2fICBAPS.2018.8527403&partnerID=40&md5=30dbb1596f4a0529332713c087bd788d}, doi = {10.1109/ICBAPS.2018.8527403}, isbn = {9781538612774}, year = {2018}, date = {2018-01-01}, journal = {2nd International Conference on BioSignal Analysis, Processing and Systems, ICBAPS 2018}, pages = {136-141}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Electroencephalography (EEG) is a measure of voltages caused due to neural activities within the brain. EEG is a recommended tool for diagnosing neurological problems because it is non-invasive and can be recorded over a longer time-period. The children with Autism Spectrum Disorder (ASD) have difficulty in expressing their emotions due to their inability of proper information processing in brain. Therefore, this research aims to build a sensory profile with the help of EEG biosignal potential to distinguish among different sensory responses. The EEG signals acquired in this research identify different emotional states such as positive-thinking or super-learning and light-relaxation and are within the frequency range of 8-12 Hertz. 64 children participated in this research among which 34 were children with ASD and 30 were normal children. The EEG data was recoded while all the children were provided with vestibular, visual, sound, taste and vestibular sensory stimulations. The raw EEG data was filtered with the help of independent component analysis (ICA) using wavelet transform and EEGLAB software. Later, for building the sensory profile, entropy approximation, means and standard deviations were extracted from the filtered EEG signals. Along with that, the filtered EEG data was also fed to a neural networks (NN) algorithm which was implemented in MATLAB. Results from the acquired EEG signals depicted that during the sensory stimulation phase, the responses of all autistic children were in an unstable state. These findings will equip and aid their learning strategy in the future. © 2018 IEEE.}, note = {cited By 0}, keywords = {Autistic Children, Biomedical Signal Processing, Brain, Children with Autism, Electroencephalography, Electrophysiology, Entropy Approximations, Independent Component Analysis, MATLAB, Neural Networks, Neurological Problems, Sensory Analysis, Sensory Profiles, Sensory Stimulation, Wavelet Packet Transforms}, pubstate = {published}, tppubtype = {conference} } Electroencephalography (EEG) is a measure of voltages caused due to neural activities within the brain. EEG is a recommended tool for diagnosing neurological problems because it is non-invasive and can be recorded over a longer time-period. The children with Autism Spectrum Disorder (ASD) have difficulty in expressing their emotions due to their inability of proper information processing in brain. Therefore, this research aims to build a sensory profile with the help of EEG biosignal potential to distinguish among different sensory responses. The EEG signals acquired in this research identify different emotional states such as positive-thinking or super-learning and light-relaxation and are within the frequency range of 8-12 Hertz. 64 children participated in this research among which 34 were children with ASD and 30 were normal children. The EEG data was recoded while all the children were provided with vestibular, visual, sound, taste and vestibular sensory stimulations. The raw EEG data was filtered with the help of independent component analysis (ICA) using wavelet transform and EEGLAB software. Later, for building the sensory profile, entropy approximation, means and standard deviations were extracted from the filtered EEG signals. Along with that, the filtered EEG data was also fed to a neural networks (NN) algorithm which was implemented in MATLAB. Results from the acquired EEG signals depicted that during the sensory stimulation phase, the responses of all autistic children were in an unstable state. These findings will equip and aid their learning strategy in the future. © 2018 IEEE. |
2017 |
Raja, P; Saringat, M Z; Mustapha, A; Zainal, A 226 (1), Institute of Physics Publishing, 2017, ISSN: 17578981, (cited By 0). Abstract | Links | BibTeX | Tags: Agile Development, Autism Spectrum Disorders, Brain, Development Activity, Digital Representations, Diseases, Education, Instant Messaging, Learning, Mobile Applications, Verbal Communication @conference{Raja2017, title = {Prospect: A Picture Exchange Communication System (PECS)-based Instant Messaging Application for Autism Spectrum Condition}, author = {P Raja and M Z Saringat and A Mustapha and A Zainal}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028640453&doi=10.1088%2f1757-899X%2f226%2f1%2f012088&partnerID=40&md5=06b8f5c7d5f5ee64b938b4aea1adfe51}, doi = {10.1088/1757-899X/226/1/012088}, issn = {17578981}, year = {2017}, date = {2017-01-01}, journal = {IOP Conference Series: Materials Science and Engineering}, volume = {226}, number = {1}, publisher = {Institute of Physics Publishing}, abstract = {Autism Spectrum Disorder (ASC) has widely gained the common attention from the public especially autistic communities. Individuals with ASC are said to have poor verbal skills and this affects them in carrying out their daily basis which they are afraid to expose themselves to the world due to their problems. ASC is diagnosed among children ranging from ages 5-12 years old and they suffer from the abnormal functioning of the brain which in turn causes lack of development activities. Thus, studies have shown that diagrammatic approaches help children with ASC to overcome their issues and improvise their visual and verbal skills. Picture Exchange Communication System or PECS consists of a series of illustrated cards and each cards has its own illustration with a caption on it. These children will understand the cards and they can compile several other cards to form sentences. This paper presents a mobile application called the Prospect, which has been developed using the agile development model for digital representation of PECS. The application is hoped to enhance the learning process and a better yielding results. © Published under licence by IOP Publishing Ltd.}, note = {cited By 0}, keywords = {Agile Development, Autism Spectrum Disorders, Brain, Development Activity, Digital Representations, Diseases, Education, Instant Messaging, Learning, Mobile Applications, Verbal Communication}, pubstate = {published}, tppubtype = {conference} } Autism Spectrum Disorder (ASC) has widely gained the common attention from the public especially autistic communities. Individuals with ASC are said to have poor verbal skills and this affects them in carrying out their daily basis which they are afraid to expose themselves to the world due to their problems. ASC is diagnosed among children ranging from ages 5-12 years old and they suffer from the abnormal functioning of the brain which in turn causes lack of development activities. Thus, studies have shown that diagrammatic approaches help children with ASC to overcome their issues and improvise their visual and verbal skills. Picture Exchange Communication System or PECS consists of a series of illustrated cards and each cards has its own illustration with a caption on it. These children will understand the cards and they can compile several other cards to form sentences. This paper presents a mobile application called the Prospect, which has been developed using the agile development model for digital representation of PECS. The application is hoped to enhance the learning process and a better yielding results. © Published under licence by IOP Publishing Ltd. |
2015 |
Khosrowabadi, R; Quek, C; Ang, K K; Wahab, A; Chen, Annabel S -H Dynamic screening of autistic children in various mental states using pattern of connectivity between brain regions Journal Article Applied Soft Computing Journal, 32 , pp. 335-346, 2015, ISSN: 15684946, (cited By 6). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Biomedical Signal Processing, Brain, Connectivity Feature, Connectivity Pattern, Diseases, Electroencephalography, Face Perceptions, Feature Extraction, Functional Connectivity, Pattern Recognition, Pattern Recognition Techniques @article{Khosrowabadi2015335, title = {Dynamic screening of autistic children in various mental states using pattern of connectivity between brain regions}, author = {R Khosrowabadi and C Quek and K K Ang and A Wahab and S -H Annabel Chen}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84927922520&doi=10.1016%2fj.asoc.2015.03.030&partnerID=40&md5=5973f80db5649e5c61e344907819a18b}, doi = {10.1016/j.asoc.2015.03.030}, issn = {15684946}, year = {2015}, date = {2015-01-01}, journal = {Applied Soft Computing Journal}, volume = {32}, pages = {335-346}, publisher = {Elsevier Ltd}, abstract = {In this study, a dynamic screening strategy is proposed to discriminate subjects with autistic spectrum disorder (ASD) from healthy controls. The ASD is defined as a neurodevelopmental disorder that disrupts normal patterns of connectivity between the brain regions. Therefore, the potential use of such abnormality for autism screening is investigated. The connectivity patterns are estimated from electroencephalogram (EEG) data collected from 8 brain regions under various mental states. The EEG data of 12 healthy controls and 6 autistic children (age matched in 7-10) were collected during eyes-open and eyes-close resting states as well as when subjects were exposed to affective faces (happy, sad and calm). Subsequently, the subjects were classified as autistic or healthy groups based on their brain connectivity patterns using pattern recognition techniques. Performance of the proposed system in each mental state is separately evaluated. The results present higher recognition rates using functional connectivity features when compared against other existing feature extraction methods. © 2015 Published by Elsevier B.V.}, note = {cited By 6}, keywords = {Autism Spectrum Disorders, Biomedical Signal Processing, Brain, Connectivity Feature, Connectivity Pattern, Diseases, Electroencephalography, Face Perceptions, Feature Extraction, Functional Connectivity, Pattern Recognition, Pattern Recognition Techniques}, pubstate = {published}, tppubtype = {article} } In this study, a dynamic screening strategy is proposed to discriminate subjects with autistic spectrum disorder (ASD) from healthy controls. The ASD is defined as a neurodevelopmental disorder that disrupts normal patterns of connectivity between the brain regions. Therefore, the potential use of such abnormality for autism screening is investigated. The connectivity patterns are estimated from electroencephalogram (EEG) data collected from 8 brain regions under various mental states. The EEG data of 12 healthy controls and 6 autistic children (age matched in 7-10) were collected during eyes-open and eyes-close resting states as well as when subjects were exposed to affective faces (happy, sad and calm). Subsequently, the subjects were classified as autistic or healthy groups based on their brain connectivity patterns using pattern recognition techniques. Performance of the proposed system in each mental state is separately evaluated. The results present higher recognition rates using functional connectivity features when compared against other existing feature extraction methods. © 2015 Published by Elsevier B.V. |
2014 |
Bhat, S; Acharya, U R; Adeli, H; Bairy, G M; Adeli, A Automated diagnosis of autism: In search of a mathematical marker Journal Article Reviews in the Neurosciences, 25 (6), pp. 851-861, 2014, ISSN: 03341763, (cited By 34). Abstract | Links | BibTeX | Tags: Algorithms, Article, Autism, Autism Spectrum Disorders, Automation, Biological Model, Brain, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Electroencephalogram, Electroencephalography, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Human, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Pathophysiology, Priority Journal, Procedures, Signal Processing, Statistical Model, Time, Time Frequency Analysis, Wavelet Analysis @article{Bhat2014851, title = {Automated diagnosis of autism: In search of a mathematical marker}, author = {S Bhat and U R Acharya and H Adeli and G M Bairy and A Adeli}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925286949&doi=10.1515%2frevneuro-2014-0036&partnerID=40&md5=04858a5c9860e9027e3113835ca2e11f}, doi = {10.1515/revneuro-2014-0036}, issn = {03341763}, year = {2014}, date = {2014-01-01}, journal = {Reviews in the Neurosciences}, volume = {25}, number = {6}, pages = {851-861}, publisher = {Walter de Gruyter GmbH}, abstract = {Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-theart review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEGbased diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder. © 2014 Walter de Gruyter GmbH.}, note = {cited By 34}, keywords = {Algorithms, Article, Autism, Autism Spectrum Disorders, Automation, Biological Model, Brain, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Electroencephalogram, Electroencephalography, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Human, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Pathophysiology, Priority Journal, Procedures, Signal Processing, Statistical Model, Time, Time Frequency Analysis, Wavelet Analysis}, pubstate = {published}, tppubtype = {article} } Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-theart review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEGbased diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder. © 2014 Walter de Gruyter GmbH. |
Bhat, S; Acharya, U R; Adeli, H; Bairy, G M; Adeli, A Autism: Cause factors, early diagnosis and therapies Journal Article Reviews in the Neurosciences, 25 (6), pp. 841-850, 2014, ISSN: 03341763, (cited By 52). Abstract | Links | BibTeX | Tags: 4 Aminobutyric Acid, Adolescent, Agenesis of Corpus Callosum, Animal Assisted Therapy, Anticonvulsive Agent, Article, Assistive Technology, Attention, Autism, Autism Spectrum Disorders, Behaviour Therapy, Biological Marker, Brain, Child Development Disorders, Children, Cognition, Cystine, Developmental Disorders, Diseases, Dolphin, Dolphin Assisted Therapy, DSM-5, Early Diagnosis, Emotion, Facial Expression, Functional Magnetic Resonance Imaging, Functional Neuroimaging, Gaze, Glutathione, Glutathione Disulfide, Human, Infant, Interpersonal Communication, Methionine, Nervous System Inflammation, Neurobiology, Neurofeedback, Oxidative Stress, Pervasive, Physiology, Preschool Child, Priority Journal, Psychoeducation, School Child, Social Interactions, Speech Therapy, Virtual Reality, Zonisamide @article{Bhat2014841, title = {Autism: Cause factors, early diagnosis and therapies}, author = {S Bhat and U R Acharya and H Adeli and G M Bairy and A Adeli}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925284617&doi=10.1515%2frevneuro-2014-0056&partnerID=40&md5=caaa32e66af70e70ec325241d01564c9}, doi = {10.1515/revneuro-2014-0056}, issn = {03341763}, year = {2014}, date = {2014-01-01}, journal = {Reviews in the Neurosciences}, volume = {25}, number = {6}, pages = {841-850}, publisher = {Walter de Gruyter GmbH}, abstract = {Autism spectrum disorder (ASD) is a complex neurobiological disorder characterized by neuropsychological and behavioral deficits. Cognitive impairment, lack of social skills, and stereotyped behavior are the major autistic symptoms, visible after a certain age. It is one of the fastest growing disabilities. Its current prevalence rate in the U.S. estimated by the Centers for Disease Control and Prevention is 1 in 68 births. The genetic and physiological structure of the brain is studied to determine the pathology of autism, but diagnosis of autism at an early age is challenging due to the existing phenotypic and etiological heterogeneity among ASD individuals. Volumetric and neuroimaging techniques are explored to elucidate the neuroanatomy of the ASD brain. Nuroanatomical, neurochemical, and neuroimaging biomarkers can help in the early diagnosis and treatment of ASD. This paper presents a review of the types of autism, etiologies, early detection, and treatment of ASD. © 2014 Walter de Gruyter GmbH.}, note = {cited By 52}, keywords = {4 Aminobutyric Acid, Adolescent, Agenesis of Corpus Callosum, Animal Assisted Therapy, Anticonvulsive Agent, Article, Assistive Technology, Attention, Autism, Autism Spectrum Disorders, Behaviour Therapy, Biological Marker, Brain, Child Development Disorders, Children, Cognition, Cystine, Developmental Disorders, Diseases, Dolphin, Dolphin Assisted Therapy, DSM-5, Early Diagnosis, Emotion, Facial Expression, Functional Magnetic Resonance Imaging, Functional Neuroimaging, Gaze, Glutathione, Glutathione Disulfide, Human, Infant, Interpersonal Communication, Methionine, Nervous System Inflammation, Neurobiology, Neurofeedback, Oxidative Stress, Pervasive, Physiology, Preschool Child, Priority Journal, Psychoeducation, School Child, Social Interactions, Speech Therapy, Virtual Reality, Zonisamide}, pubstate = {published}, tppubtype = {article} } Autism spectrum disorder (ASD) is a complex neurobiological disorder characterized by neuropsychological and behavioral deficits. Cognitive impairment, lack of social skills, and stereotyped behavior are the major autistic symptoms, visible after a certain age. It is one of the fastest growing disabilities. Its current prevalence rate in the U.S. estimated by the Centers for Disease Control and Prevention is 1 in 68 births. The genetic and physiological structure of the brain is studied to determine the pathology of autism, but diagnosis of autism at an early age is challenging due to the existing phenotypic and etiological heterogeneity among ASD individuals. Volumetric and neuroimaging techniques are explored to elucidate the neuroanatomy of the ASD brain. Nuroanatomical, neurochemical, and neuroimaging biomarkers can help in the early diagnosis and treatment of ASD. This paper presents a review of the types of autism, etiologies, early detection, and treatment of ASD. © 2014 Walter de Gruyter GmbH. |
2012 |
Hoole, P R P; Pirapaharan, K; Basar, S A; Ismail, R; Liyanage, D L D A; Senanayake, S S H M U L; Hoole, S R H Autism, EEG and brain electromagnetics research Conference 2012, ISBN: 9781467316668, (cited By 11). Abstract | Links | BibTeX | Tags: Biomedical Engineering, Brain, Brain Regions, Classification Accuracy, Diseases, EEG Signals, Electromagnetic Signals, Electromagnetics, Electromagnetism, Frequency Domains, International Group, Multilayer Perception Neural Networks, Neuroimaging, Principal Component Analysis @conference{Hoole2012541, title = {Autism, EEG and brain electromagnetics research}, author = {P R P Hoole and K Pirapaharan and S A Basar and R Ismail and D L D A Liyanage and S S H M U L Senanayake and S R H Hoole}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876771339&doi=10.1109%2fIECBES.2012.6498036&partnerID=40&md5=9f9390b30b859a90936c66699c1a5115}, doi = {10.1109/IECBES.2012.6498036}, isbn = {9781467316668}, year = {2012}, date = {2012-01-01}, journal = {2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012}, pages = {541-543}, abstract = {There has been a significant increase in the incidence of autism. We report the work on autism by our international group, on the growing attention paid to EEG based diagnosis and the interest in tracing EEG changes to brain electromagnetic signals (BEMS), seeking the cause of autism and the brain regions of its origin. The time- and frequency domain and principal component analysis (PCA) of these EEG signals with a Multilayer Perception Neural Network (MLP) identifies an autistic subject and helps improve classification accuracy. We show differences between a working brain and a relaxed brain, especially in the Alpha waves used for diagnosis. © 2012 IEEE.}, note = {cited By 11}, keywords = {Biomedical Engineering, Brain, Brain Regions, Classification Accuracy, Diseases, EEG Signals, Electromagnetic Signals, Electromagnetics, Electromagnetism, Frequency Domains, International Group, Multilayer Perception Neural Networks, Neuroimaging, Principal Component Analysis}, pubstate = {published}, tppubtype = {conference} } There has been a significant increase in the incidence of autism. We report the work on autism by our international group, on the growing attention paid to EEG based diagnosis and the interest in tracing EEG changes to brain electromagnetic signals (BEMS), seeking the cause of autism and the brain regions of its origin. The time- and frequency domain and principal component analysis (PCA) of these EEG signals with a Multilayer Perception Neural Network (MLP) identifies an autistic subject and helps improve classification accuracy. We show differences between a working brain and a relaxed brain, especially in the Alpha waves used for diagnosis. © 2012 IEEE. |
Cheah, P -S; Ramshaw, H S; Thomas, P Q; Toyo-Oka, K; Xu, X; Martin, S; Coyle, P; Guthridge, M A; Stomski, F; Buuse, Van Den M; Wynshaw-Boris, A; Lopez, A F; Schwarz, Q P Neurodevelopmental and neuropsychiatric behaviour defects arise from 14-3-3ζ deficiency Journal Article Molecular Psychiatry, 17 (4), pp. 451-466, 2012, ISSN: 13594184, (cited By 58). Abstract | Links | BibTeX | Tags: 14-3-3 Proteins, Animal Experiment, Animal Model, Animal Tissue, Animals, Article, Autism, Behaviour Disorder, Bipolar Disorder, Brain, Cell Movement, Cells, Cognitive Defect, Controlled Study, Cultured, Disease Models, Disrupted in Schizophrenia 1 Protein, Embryo, Female, Gene, Gene Deletion, Genetic Predisposition to Disease, Glutamic Acid, Hippocampal Mossy Fiber, Hippocampus, Human, Hyperactivity, Inbred C57BL, Isoprotein, Knockout, Learning, Male, Maze Learning, Memory, Mice, Motor Activity, Mouse, Neurogenesis, Neuronal Migration Disorder, Neurons, Neuropsychiatry, Nonhuman, Priority Journal, Protein 14-3-3, Protein 14-3-3 Zeta, Protein Deficiency, Protein Interaction, Recognition, Risk Factor, Schizophrenia, Sensory Gating, Synapse, Unclassified Drug @article{Cheah2012451, title = {Neurodevelopmental and neuropsychiatric behaviour defects arise from 14-3-3ζ deficiency}, author = {P -S Cheah and H S Ramshaw and P Q Thomas and K Toyo-Oka and X Xu and S Martin and P Coyle and M A Guthridge and F Stomski and M Van Den Buuse and A Wynshaw-Boris and A F Lopez and Q P Schwarz}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859007028&doi=10.1038%2fmp.2011.158&partnerID=40&md5=7f507fef31a192a10b3cde7bf69b5442}, doi = {10.1038/mp.2011.158}, issn = {13594184}, year = {2012}, date = {2012-01-01}, journal = {Molecular Psychiatry}, volume = {17}, number = {4}, pages = {451-466}, abstract = {Complex neuropsychiatric disorders are believed to arise from multiple synergistic deficiencies within connected biological networks controlling neuronal migration, axonal pathfinding and synapse formation. Here, we show that deletion of 14-3-3ζ causes neurodevelopmental anomalies similar to those seen in neuropsychiatric disorders such as schizophrenia, autism spectrum disorder and bipolar disorder. 14-3-3ζ-Deficient mice displayed striking behavioural and cognitive deficiencies including a reduced capacity to learn and remember, hyperactivity and disrupted sensorimotor gating. These deficits are accompanied by subtle developmental abnormalities of the hippocampus that are underpinned by aberrant neuronal migration. Significantly, 14-3-3ζ- deficient mice exhibited abnormal mossy fibre navigation and glutamatergic synapse formation. The molecular basis of these defects involves the schizophrenia risk factor, DISC1, which interacts isoform specifically with 14-3-3ζ. Our data provide the first evidence of a direct role for 14-3-3ζ deficiency in the aetiology of neurodevelopmental disorders and identifies 14-3-3ζ as a central risk factor in the schizophrenia protein interaction network. © 2012 Macmillan Publishers Limited All rights reserved.}, note = {cited By 58}, keywords = {14-3-3 Proteins, Animal Experiment, Animal Model, Animal Tissue, Animals, Article, Autism, Behaviour Disorder, Bipolar Disorder, Brain, Cell Movement, Cells, Cognitive Defect, Controlled Study, Cultured, Disease Models, Disrupted in Schizophrenia 1 Protein, Embryo, Female, Gene, Gene Deletion, Genetic Predisposition to Disease, Glutamic Acid, Hippocampal Mossy Fiber, Hippocampus, Human, Hyperactivity, Inbred C57BL, Isoprotein, Knockout, Learning, Male, Maze Learning, Memory, Mice, Motor Activity, Mouse, Neurogenesis, Neuronal Migration Disorder, Neurons, Neuropsychiatry, Nonhuman, Priority Journal, Protein 14-3-3, Protein 14-3-3 Zeta, Protein Deficiency, Protein Interaction, Recognition, Risk Factor, Schizophrenia, Sensory Gating, Synapse, Unclassified Drug}, pubstate = {published}, tppubtype = {article} } Complex neuropsychiatric disorders are believed to arise from multiple synergistic deficiencies within connected biological networks controlling neuronal migration, axonal pathfinding and synapse formation. Here, we show that deletion of 14-3-3ζ causes neurodevelopmental anomalies similar to those seen in neuropsychiatric disorders such as schizophrenia, autism spectrum disorder and bipolar disorder. 14-3-3ζ-Deficient mice displayed striking behavioural and cognitive deficiencies including a reduced capacity to learn and remember, hyperactivity and disrupted sensorimotor gating. These deficits are accompanied by subtle developmental abnormalities of the hippocampus that are underpinned by aberrant neuronal migration. Significantly, 14-3-3ζ- deficient mice exhibited abnormal mossy fibre navigation and glutamatergic synapse formation. The molecular basis of these defects involves the schizophrenia risk factor, DISC1, which interacts isoform specifically with 14-3-3ζ. Our data provide the first evidence of a direct role for 14-3-3ζ deficiency in the aetiology of neurodevelopmental disorders and identifies 14-3-3ζ as a central risk factor in the schizophrenia protein interaction network. © 2012 Macmillan Publishers Limited All rights reserved. |