@article{Al-Hiyali201886,
title = {A review in modification food-intake behavior by brain stimulation: Excess weight cases},
author = {M I Al-Hiyali and A J Ishak and H Harun and S A Ahmad and W A Wan Sulaiman},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062843670&doi=10.14704%2fnq.2018.16.12.1894&partnerID=40&md5=235f66cef05a144be23472641f70bd1d},
doi = {10.14704/nq.2018.16.12.1894},
issn = {13035150},
year = {2018},
date = {2018-01-01},
journal = {NeuroQuantology},
volume = {16},
number = {12},
pages = {86-97},
publisher = {Anka Publishers},
abstract = {Obesity and overweight are frequently prescribed for dysfunction in food-intake behavior. Due to the widely prevalence of obesity in last year’s, there is demand for more studies which are aimed to modify the food-intake behavior. For the past decades many researches has applied in modify food-intake by brain training or stimulation. This review for neuroscience studies in modifying food-intake behavior, it’s involved three sections; The first section explained the role of brain activity in food-intake regulation, general ideas about biomedical devices in food-intake behavior are discussed in second section and third section focused on brain-stimulation systems. Finally, this paper concluded with main points that need to be taken into account when designing experimental study for modification food-intake behavior by brain stimulation according to previous studies recommendation and challenges. © 2018, Anka Publishers. All Rights Reserved.},
note = {cited By 2},
keywords = {Amygdala, Anoxia, Article, Autism, Binge Eating Disorder, Body Mass, Body Weight, Brain Depth Stimulation, Depolarization, Dietary Intake, Drug Craving, Eating Disorder, Electric Current, Electroencephalogram, Electroencephalography, Energy Consumption, Energy Expenditure, Feeding Behavior, Food Intake, Functional Magnetic Resonance Imaging, Gender, Health Status, Homeostasis, Human, Hunger, Lifestyle, Nerve Cell Membrane Steady Potential, Nerve Excitability, Neurofeedback, Neuromodulation, Nutritional Assessment, Outcome Assessment, Questionnaires, Repetitive Transcranial Magnetic Stimulation, Signal Processing, Training, Transcranial Direct Current Stimulation, Transcranial Magnetic Stimulation, Underweight},
pubstate = {published},
tppubtype = {article}
}

@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}
}

@article{Paudel2018145,
title = {Role of inflammation in epilepsy and neurobehavioral comorbidities: Implication for therapy},
author = {Y N Paudel and M F Shaikh and S Shah and Y Kumari and I Othman},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053082063&doi=10.1016%2fj.ejphar.2018.08.020&partnerID=40&md5=27ff0199bae72f156425637a7ad02228},
doi = {10.1016/j.ejphar.2018.08.020},
issn = {00142999},
year = {2018},
date = {2018-01-01},
journal = {European Journal of Pharmacology},
volume = {837},
pages = {145-155},
publisher = {Elsevier B.V.},
abstract = {Epilepsy is a devastating condition affecting around 70 million people worldwide. Moreover, the quality of life of people with epilepsy (PWE) is worsened by a series of comorbidities. The neurobehavioral comorbidities discussed herein share a reciprocal and complex relationship with epilepsy, which ultimately complicates the treatment process in PWE. Understanding the mechanistic pathway by which these comorbidities are associated with epilepsy might be instrumental in developing therapeutic interventions. Inflammatory cytokine signaling in the brain regulates important brain functions including neurotransmitter metabolism, neuroendocrine function, synaptic plasticity, dopaminergic transmission, the kynurenine pathway, and affects neurogenesis as well as the neural circuitry of moods. In this review, we hypothesize that the complex relationship between epilepsy and its related comorbidities (cognitive impairment, depression, anxiety, autism, and schizophrenia) can be unraveled through the inflammatory mechanism that plays a prominent role in all these individual conditions. An ample amount of evidence is available reporting the role of inflammation in epilepsy and all individual comorbid condition but their complex relationship with epilepsy has not yet been explored through the prospective of inflammatory pathway. Our review suggests that epilepsy and its neurobehavioral comorbidities are associated with elevated levels of several key inflammatory markers. This review also sheds light on the mechanistic association between epilepsy and its neurobehavioral comorbidities. Moreover, we analyzed several anti-inflammatory therapies available for epilepsy and its neurobehavioral comorbidities. We suggest, these anti-inflammatory therapies might be a possible intervention and could be a promising strategy for preventing epileptogenesis and its related neurobehavioral comorbidities. © 2018 Elsevier B.V.},
note = {cited By 14},
keywords = {3 Dioxygenase, Acetylsalicylic Acid, Adalimumab, Anakinra, Animals, Anti-Inflammatory Agents, Anxiety, Autacoid, Autism, Autism Spectrum Disorders, Behaviour Disorder, Belnacasan, Celecoxib, Cognition, Comorbidity, Complication, Cyclooxygenase 2, Cyclooxygenase 2 Inhibitor, Cytokine, Cytokines, Depression, Dexmedetomidine, Disease Association, Dopaminergic Transmission, Electroencephalogram, Electroencephalography, Epilepsy, Epileptogenesis, Esculetin, High Mobility Group B1 Protein, Human, Ibuprofen, Icariin, IImmunoglobulin Enhancer Binding Protein, Immunology, Indoleamine 2, Inflammation, Inflammation Mediators, Infliximab, Interleukin 1beta, Interleukin 6, Minocycline, Nerve Cell Plasticity, Nervous System Development, Nervous System Inflammation, Neuroendocrine Regulation, Neurotransmitter Release, Nonhuman, Palmidrol, Paracetamol, Physiology, Priority Journal, Prostaglandin E2, Psychology, Review, SC 51089, Schizophrenia, Toll-Like Receptor 4, Transforming Growth Factor Beta, Tryptophan Hydroxylase, Tumor Necrosis Factor, Unclassified Drug},
pubstate = {published},
tppubtype = {article}
}

@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}
}

@article{Modugumudi2013321,
title = {Efficacy of collaborative virtual environment intervention programs in emotion expression of children with autism},
author = {Y R Modugumudi and J Santhosh and S Anand},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881262807&doi=10.1166%2fjmihi.2013.1167&partnerID=40&md5=c8e767c8eba2bbbec5ff36a43eb59af6},
doi = {10.1166/jmihi.2013.1167},
issn = {21567018},
year = {2013},
date = {2013-01-01},
journal = {Journal of Medical Imaging and Health Informatics},
volume = {3},
number = {2},
pages = {321-325},
abstract = {Exploratory empirical studies on Collaborative Virtual Environments (CVEs) were conducted to determine if children with autism could make basic emotional recognition effectively, with the use of CVEs as assistive technology. In this paper we report the results of electro-physiological study of two groups of autistic children after an intervention program with and without using Collaborative Virtual Environment. The group trained with CVE showed better results compared to the group trained without Collaborative virtual Environment. There is an emphasized early emotion expression positivity component at around 120 ms latency for CVE trained group which clearly distinguishes the CVE untrained group. Also there are differences observed in Event Related Potential component at about 170 ms latency after the stimulus. Results indicate that the Collaborative Virtual Environments are effective in training Autistic children. © 2013 American Scientific Publishers.},
note = {cited By 4},
keywords = {Adolescent, Adult, Article, Autism, Children, Clinical Article, Collaborative Virtual Environment, Controlled Study, DSM-IV, Electroencephalogram, Electroencephalography, Electrooculogram, Emotion, Environment, Event Related Potential, Facial Expression, Female, Human, Latent Period, Male, Recognition, School Child},
pubstate = {published},
tppubtype = {article}
}

@article{Tan2012123,
title = {Generalized epilepsy with febrile seizure plus (GEFS+) spectrum: Novel de novo mutation of SCN1A detected in a Malaysian patient},
author = {E H Tan and A A M Yusoff and J M Abdullah and S A Razak},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870194979&doi=10.4103%2f1817-1745.102575&partnerID=40&md5=b73f0bdb583e84404e0fff232faf30cb},
doi = {10.4103/1817-1745.102575},
issn = {18171745},
year = {2012},
date = {2012-01-01},
journal = {Journal of Pediatric Neurosciences},
volume = {7},
number = {2},
pages = {123-125},
abstract = {In this report, we describe a 15-year-old Malaysian male patient with a de novo SCN1A mutation who experienced prolonged febrile seizures after his first seizure at 6 months of age. This boy had generalized tonic clonic seizure (GTCS) which occurred with and without fever. Sequencing analysis of voltage-gated sodium channel a1-subunit gene, SCN1A, confirmed a homozygous A to G change at nucleotide 5197 (c.5197A > G) in exon 26 resulting in amino acid substitution of asparagines to aspartate at codon 1733 of sodium channel. The mutation identified in this patient is located in the pore-forming loop of SCN1A and this case report suggests missense mutation in pore-forming loop causes generalized epilepsy with febrile seizure plus (GEFS+) with clinically more severe neurologic phenotype including intellectual disabilities (mental retardation and autism features) and neuropsychiatric disease (anxiety disorder).},
note = {cited By 3},
keywords = {Adolescent, Anxiety Disorder, Article, Autism, Carbamazepine, Case Report, Computer Assisted Tomography, Electroencephalogram, Electroencephalography, Febrile Convulsion, Gene, Generalized Epilepsy, Generalized Epilepsy with Febrile Seizure Plus, Human, Karyotype, Malaysia, Male, Medical History, Mental Deficiency, Missense Mutation, Nuclear Magnetic Resonance Imaging, Phenotype, SCN1A Gene, Tonic Clonic Seizure, Topiramate, Valproic Acid},
pubstate = {published},
tppubtype = {article}
}