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Fard YA, Sadeghi EN, Pajoohesh Z, Gharehdaghi Z, Khatibi DM, Khosravifar S, Pishkari Y, Nozari S, Hijazi A, Pakmehr S, Shayan SK. Epigenetic underpinnings of the autistic mind: Histone modifications and prefrontal excitation/inhibition imbalance. Am J Med Genet B Neuropsychiatr Genet 2024:e32986. [PMID: 38837296 DOI: 10.1002/ajmg.b.32986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 03/30/2024] [Accepted: 04/25/2024] [Indexed: 06/07/2024]
Abstract
Autism spectrum disorder (ASD) is complex neurobehavioral condition influenced by several cellular and molecular mechanisms that are often concerned with synaptogenesis and synaptic activity. Based on the excitation/inhibition (E/I) imbalance theory, ASD could be the result of disruption in excitatory and inhibitory synaptic transmission across the brain. The prefrontal cortex (PFC) is the chief regulator of executive function and can be affected by altered neuronal excitation and inhibition in the course of ASD. The molecular mechanisms involved in E/I imbalance are subject to epigenetic regulation. In ASD, altered enrichment and spreading of histone H3 and H4 modifications such as the activation-linked H3K4me2/3, H3K9ac, and H3K27ac, and repression-linked H3K9me2, H3K27me3, and H4K20me2 in the PFC result in dysregulation of molecules mediating synaptic excitation (ARC, EGR1, mGluR2, mGluR3, GluN2A, and GluN2B) and synaptic inhibition (BSN, EphA7, SLC6A1). Histone modifications are a dynamic component of the epigenetic regulatory elements with a pronounced effect on patterns of gene expression with regards to any biological process. The excitation/inhibition imbalance associated with ASD is based on the excitatory and inhibitory synaptic activity in different regions of the brain, including the PFC, the ultimate outcome of which is highly influenced by transcriptional activity of relevant genes.
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Affiliation(s)
| | | | - Zohreh Pajoohesh
- Faculty of Medicine, Zabol Univeristy of Medical Sciences, Zabol, Iran
| | - Zahra Gharehdaghi
- Department of Pharmacology, Zabol University of Medical Sciences, Zabol, Iran
| | | | | | - Yasamin Pishkari
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Shadi Nozari
- School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Ahmed Hijazi
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | | | - Sepideh Karkon Shayan
- Student Research Committee, School of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran
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Matsuba ESM, Prieve BA, Cary E, Pacheco D, Madrid A, McKernan E, Kaplan-Kahn E, Russo N. A Preliminary Study Characterizing Subcortical and Cortical Auditory Processing and Their Relation to Autistic Traits and Sensory Features. J Autism Dev Disord 2024; 54:75-92. [PMID: 36227444 PMCID: PMC9559145 DOI: 10.1007/s10803-022-05773-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2022] [Indexed: 11/23/2022]
Abstract
This study characterizes the subcortical auditory brainstem response (speech-ABR) and cortical auditory processing (P1 and Mismatch Negativity; MMN) to speech sounds and their relationship to autistic traits and sensory features within the same group of autistic children (n = 10) matched on age and non-verbal IQ to their typically developing (TD) peers (n = 21). No speech-ABR differences were noted, but autistic individuals had larger P1 and faster MMN responses. Correlations revealed that larger P1 amplitudes and MMN responses were associated with greater autistic traits and more sensory features. These findings highlight the complexity of the auditory system and its relationships to behaviours in autism, while also emphasizing the importance of measurement and developmental matching.
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Affiliation(s)
- Erin S. M. Matsuba
- Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13079 USA
| | - Beth A. Prieve
- Department of Communication Sciences and Disorders, Syracuse University, 1200 Skytop Road, Syracuse, NY 13079 USA
| | - Emily Cary
- Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13079 USA
| | - Devon Pacheco
- Department of Communication Sciences and Disorders, Syracuse University, 1200 Skytop Road, Syracuse, NY 13079 USA
| | - Angela Madrid
- Department of Communication Sciences and Disorders, Syracuse University, 1200 Skytop Road, Syracuse, NY 13079 USA
| | - Elizabeth McKernan
- Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13079 USA
| | - Elizabeth Kaplan-Kahn
- Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13079 USA
| | - Natalie Russo
- Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13079 USA
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Daikoku T, Kamermans K, Minatoya M. Exploring cognitive individuality and the underlying creativity in statistical learning and phase entrainment. EXCLI JOURNAL 2023; 22:828-846. [PMID: 37720236 PMCID: PMC10502202 DOI: 10.17179/excli2023-6135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 08/02/2023] [Indexed: 09/19/2023]
Abstract
Statistical learning starts at an early age and is intimately linked to brain development and the emergence of individuality. Through such a long period of statistical learning, the brain updates and constructs statistical models, with the model's individuality changing based on the type and degree of stimulation received. However, the detailed mechanisms underlying this process are unknown. This paper argues three main points of statistical learning, including 1) cognitive individuality based on "reliability" of prediction, 2) the construction of information "hierarchy" through chunking, and 3) the acquisition of "1-3Hz rhythm" that is essential for early language and music learning. We developed a Hierarchical Bayesian Statistical Learning (HBSL) model that takes into account both reliability and hierarchy, mimicking the statistical learning processes of the brain. Using this model, we conducted a simulation experiment to visualize the temporal dynamics of perception and production processes through statistical learning. By modulating the sensitivity to sound stimuli, we simulated three cognitive models with different reliability on bottom-up sensory stimuli relative to top-down prior prediction: hypo-sensitive, normal-sensitive, and hyper-sensitive models. We suggested that statistical learning plays a crucial role in the acquisition of 1-3 Hz rhythm. Moreover, a hyper-sensitive model quickly learned the sensory statistics but became fixated on their internal model, making it difficult to generate new information, whereas a hypo-sensitive model has lower learning efficiency but may be more likely to generate new information. Various individual characteristics may not necessarily confer an overall advantage over others, as there may be a trade-off between learning efficiency and the ease of generating new information. This study has the potential to shed light on the heterogeneous nature of statistical learning, as well as the paradoxical phenomenon in which individuals with certain cognitive traits that impede specific types of perceptual abilities exhibit superior performance in creative contexts.
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Affiliation(s)
- Tatsuya Daikoku
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
- Centre for Neuroscience in Education, University of Cambridge, Cambridge, UK
- Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, Hiroshima, Japan
| | - Kevin Kamermans
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Maiko Minatoya
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
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Mayerle MCCDS, Riesgo R, Gregory L, Borges VMS, Sleifer P. Mismatch Negativity in Children and Adolescents with Autism Spectrum Disorder. Int Arch Otorhinolaryngol 2023; 27:e218-e225. [PMID: 37125353 PMCID: PMC10147454 DOI: 10.1055/s-0043-1768209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 08/29/2021] [Indexed: 05/02/2023] Open
Abstract
Introduction Individuals with autism spectrum disorder (ASD) have abnormalities in auditory perception and sensitivity. The mismatch negativity (MMN) component of the evoked potential demonstrates a brain detection response to an auditory change due to memory, and enables the identification of changes in the auditory system. Objective To analyze MMN responses in children and adolescents with ASD and compare them with those of a control group. Methods Cross-sectional and comparative study. The sample was composed of 68 children and adolescents, divided into study group (SG), which contained those diagnosed with ASD, and the control group (CG), which contained those with typical development, normal hearing thresholds, and without hearing complaints. All participants were submitted to peripheral and central electrophysiological auditory evaluations. For the electrophysiological auditory evaluation and MMN recording, the electrodes were fixed in the following positions: Fz (active electrode), M1 and M2 (reference electrodes), and on the forehead (ground electrode). Auditory stimuli were presented in both ears simultaneously, with a frequency of 1,000 Hz for the frequent stimulus, and of 2,000 Hz for the rare stimulus, in an intensity of 80 dBNA. Results Latency and amplitude values were increased in the SG, with a statistically significant difference in comparison with the CG. In the MMN analysis, there was no statistically significant difference in the comparison between right and left ears and between genders. Conclusion Children and adolescents with ASD had higher latency and amplitude values in the MMN component than the individuals in the CG.
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Affiliation(s)
- Maria Clara Clack da Silva Mayerle
- Departamento de Patologia, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
- Address for correspondence Maria Clara Clack da Silva Mayerle, Bachelor Departamento de Patologia, Universidade Federal de Ciências da Saúde de Porto AlegrePorto Alegre, Rio Grande do Sul 90035-003Brazil
| | - Rudimar Riesgo
- Departamento de Pediatria, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Letícia Gregory
- Departamento de Patologia, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Viviann Magalhães Silva Borges
- Departamento de Saúde e Comunicação Humana, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Pricila Sleifer
- Departamento de Saúde e Comunicação Humana, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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Han C, Guo M, Ke X, Zeng L, Li M, Haihambo N, Lu J, Wang L, Wei P. Oscillatory biomarkers of autism: evidence from the innate visual fear evoking paradigm. Cogn Neurodyn 2023; 17:459-466. [PMID: 37007195 PMCID: PMC10050250 DOI: 10.1007/s11571-022-09839-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 06/15/2022] [Accepted: 06/20/2022] [Indexed: 11/03/2022] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with multiple associated deficits in both social and cognitive functioning. Diagnosing ASD usually relies on subjective clinical competencies, and research on objective criteria for diagnosing ASD in the early stage is still in its infancy. A recent animal study showed that the looming-evoked defensive response was impaired in mice with ASD, but whether the effect will be observed in human and contribute to finding a robust clinical neural biomarker remain unclear. Here, to investigate the looming-evoked defense response in humans, electroencephalogram responses toward looming and corresponding control stimuli (far and missing type) were recorded in children with ASD and typical developed (TD) children. Results revealed that alpha-band activity in the posterior brain region was strongly suppressed after looming stimuli in the TD group, but remained unchanged in the ASD group. This method could be a novel, objective way to detect ASD earlier. These findings suggest that further investigation of the neural mechanism underlying innate fear from the oscillatory view could be a helpful direction in the future. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09839-6.
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Affiliation(s)
- Chuanliang Han
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055 China
| | - Mingrou Guo
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055 China
| | - Xiaoyin Ke
- Department of Child Psychiatry, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, China
| | - Lanting Zeng
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055 China
| | - Meijia Li
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Naem Haihambo
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Jianping Lu
- Department of Child Psychiatry, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, China
| | - Liping Wang
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Pengfei Wei
- Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen Fundamental Research Institutions, Shenzhen, 518055 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
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Kabil SE, Abdelshafy R, Ahmed AIA, Zahran AM, Attalah M, Sallam Y, El Lateef AGA. Mismatch Negativity and Auditory Brain Stem Response in Children with Autism Spectrum Disorders and Language Disorders. J Multidiscip Healthc 2023; 16:811-817. [PMID: 37006341 PMCID: PMC10065014 DOI: 10.2147/jmdh.s401937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 03/03/2023] [Indexed: 03/29/2023] Open
Abstract
Objective Language disorders (LD) in autism spectrum disorders (ASD) are highly variable and has a severe impact on the level of functioning in autistic children. Early diagnosis of these language disorders is essential for early interventions for children at risk. The electrophysiological measurements are considered valuable tools for determining language disabilities in children with ASD. This study aimed to study and compare ABR and MMN in autistic children with language disorders. Methods This study included a group of typically developing children and a group of children diagnosed with autistic spectrum disorders and language disorders. Both groups were matching according to age and gender. After confirming bilateral normal peripheral hearing sensitivity, ABR was done and both absolute and interpeak wave latencies were correlated. MMN using frequency oddball paradigms were also obtained and correlated. Results More abnormalities were reported in ABR test results in the form of delayed absolute latencies and prolonged interpeak intervals. Also, we reported prolonged latencies of MMN. Consequently, both ABR and MMN are complementary test in evaluating autistic children with language disorders. Conclusion Our results support the hypothesis of remarkable dysfunction in basic auditory sound processing that may impact the linguistic development of autistic children.
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Affiliation(s)
- Shaimaa E Kabil
- E. N. T Department, Faculty of Medicine Cairo, Al-Azhar University, Cairo, Egypt
- Correspondence: Shaimaa E Kabil, Email
| | - Rania Abdelshafy
- E. N. T Department, Faculty of Medicine Cairo, Al-Azhar University, Cairo, Egypt
| | | | | | - Mahmoud Attalah
- Pediatric Department, Faculty of Medicine Cairo, Al-Azhar University, Cairo, Egypt
| | - Yossra Sallam
- E. N. T Department, Faculty of Medicine Cairo, Al-Azhar University, Cairo, Egypt
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Gonçalves AM, Monteiro P. Autism Spectrum Disorder and auditory sensory alterations: a systematic review on the integrity of cognitive and neuronal functions related to auditory processing. J Neural Transm (Vienna) 2023; 130:325-408. [PMID: 36914900 PMCID: PMC10033482 DOI: 10.1007/s00702-023-02595-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 01/17/2023] [Indexed: 03/15/2023]
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with a wide spectrum of symptoms, mainly characterized by social, communication, and cognitive impairments. Latest diagnostic criteria according to DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, 2013) now include sensory issues among the four restricted/repetitive behavior features defined as "hyper- or hypo-reactivity to sensory input or unusual interest in sensory aspects of environment". Here, we review auditory sensory alterations in patients with ASD. Considering the updated diagnostic criteria for ASD, we examined research evidence (2015-2022) of the integrity of the cognitive function in auditory-related tasks, the integrity of the peripheral auditory system, and the integrity of the central nervous system in patients diagnosed with ASD. Taking into account the different approaches and experimental study designs, we reappraise the knowledge on auditory sensory alterations and reflect on how these might be linked with behavior symptomatology in ASD.
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Affiliation(s)
- Ana Margarida Gonçalves
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's-PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
| | - Patricia Monteiro
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
- ICVS/3B's-PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.
- Experimental Biology Unit, Department of Biomedicine, Faculty of Medicine, University of Porto, Porto, Portugal.
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Daikoku T, Wiggins GA, Nagai Y. Statistical Properties of Musical Creativity: Roles of Hierarchy and Uncertainty in Statistical Learning. Front Neurosci 2021; 15:640412. [PMID: 33958983 PMCID: PMC8093513 DOI: 10.3389/fnins.2021.640412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 03/10/2021] [Indexed: 12/18/2022] Open
Abstract
Creativity is part of human nature and is commonly understood as a phenomenon whereby something original and worthwhile is formed. Owing to this ability, humans can produce innovative information that often facilitates growth in our society. Creativity also contributes to esthetic and artistic productions, such as music and art. However, the mechanism by which creativity emerges in the brain remains debatable. Recently, a growing body of evidence has suggested that statistical learning contributes to creativity. Statistical learning is an innate and implicit function of the human brain and is considered essential for brain development. Through statistical learning, humans can produce and comprehend structured information, such as music. It is thought that creativity is linked to acquired knowledge, but so-called "eureka" moments often occur unexpectedly under subconscious conditions, without the intention to use the acquired knowledge. Given that a creative moment is intrinsically implicit, we postulate that some types of creativity can be linked to implicit statistical knowledge in the brain. This article reviews neural and computational studies on how creativity emerges within the framework of statistical learning in the brain (i.e., statistical creativity). Here, we propose a hierarchical model of statistical learning: statistically chunking into a unit (hereafter and shallow statistical learning) and combining several units (hereafter and deep statistical learning). We suggest that deep statistical learning contributes dominantly to statistical creativity in music. Furthermore, the temporal dynamics of perceptual uncertainty can be another potential causal factor in statistical creativity. Considering that statistical learning is fundamental to brain development, we also discuss how typical versus atypical brain development modulates hierarchical statistical learning and statistical creativity. We believe that this review will shed light on the key roles of statistical learning in musical creativity and facilitate further investigation of how creativity emerges in the brain.
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Affiliation(s)
- Tatsuya Daikoku
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan
| | - Geraint A. Wiggins
- AI Lab, Vrije Universiteit Brussel, Brussels, Belgium
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom
| | - Yukie Nagai
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan
- Institute for AI and Beyond, The University of Tokyo, Tokyo, Japan
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Leung JH, Purdy SC, Corballis PM. Improving Emotion Perception in Children with Autism Spectrum Disorder with Computer-Based Training and Hearing Amplification. Brain Sci 2021; 11:469. [PMID: 33917776 PMCID: PMC8068114 DOI: 10.3390/brainsci11040469] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 03/22/2021] [Accepted: 04/06/2021] [Indexed: 11/16/2022] Open
Abstract
Individuals with Autism Spectrum Disorder (ASD) experience challenges with social communication, often involving emotional elements of language. This may stem from underlying auditory processing difficulties, especially when incoming speech is nuanced or complex. This study explored the effects of auditory training on social perception abilities of children with ASD. The training combined use of a remote-microphone hearing system and computerized emotion perception training. At baseline, children with ASD had poorer social communication scores and delayed mismatch negativity (MMN) compared to typically developing children. Behavioral results, measured pre- and post-intervention, revealed increased social perception scores in children with ASD to the extent that they outperformed their typically developing peers post-intervention. Electrophysiology results revealed changes in neural responses to emotional speech stimuli. Post-intervention, mismatch responses of children with ASD more closely resembled their neurotypical peers, with shorter MMN latencies, a significantly heightened P2 wave, and greater differentiation of emotional stimuli, consistent with their improved behavioral results. This study sets the foundation for further investigation into connections between auditory processing difficulties and social perception and communication for individuals with ASD, and provides a promising indication that combining amplified hearing and computer-based targeted social perception training using emotional speech stimuli may have neuro-rehabilitative benefits.
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Affiliation(s)
- Joan H. Leung
- School of Psychology, The University of Auckland, Auckland 1023, New Zealand; (S.C.P.); (P.M.C.)
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Kaur I, Behl T, Aleya L, Rahman MH, Kumar A, Arora S, Akter R. Role of metallic pollutants in neurodegeneration: effects of aluminum, lead, mercury, and arsenic in mediating brain impairment events and autism spectrum disorder. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:8989-9001. [PMID: 33447979 DOI: 10.1007/s11356-020-12255-0] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 12/27/2020] [Indexed: 04/16/2023]
Abstract
Autism spectrum disorder (ASD) is a developmental disorder of the brain characterized by shortfall in the social portfolio of an individual and abbreviated interactive and communication aspects rendering stereotypical behavior and pitfalls in a child's memory, thinking, and learning capabilities. The incidence of ASD has accelerated since the past decade, portraying environment as one of the primary assets, comprising of metallic components aiming to curb the neurodevelopmental pathways in an individual. Many regulations like Clean Air Act and critical steps taken by countries all over the globe, like Sweden and the USA, have rendered the necessity to study the effects of environmental metallic components on ASD progression. The review focuses on the primary metallic components present in the environment (aluminum, lead, mercury, and arsenic), responsible for accelerating ASD symptoms by a set of general mechanisms like oxidative stress reduction, glycolysis suppression, microglial activation, and metalloprotein disruption, resulting in apoptotic signaling, neurotoxic effects, and neuroinflammatory responses. The effect of these metals can be retarded by certain protective strategies like chelation, dietary correction, certain agents (curcumin, mangiferin, selenium), and detoxification enhancement, which can necessarily halt the neurodegenerative effects.
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Affiliation(s)
- Ishnoor Kaur
- Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India
| | - Tapan Behl
- Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India.
| | - Lotfi Aleya
- Chrono-Environnement Laboratory, UMR CNRS 6249, Bourgogne Franche-Comté University, Paris, France
| | - Md Habibur Rahman
- Department of Global Medical Science, Wonju College of Medicine, Yonsei University, Seoul, South Korea
- Department of Pharmacy, Southeast University, Banani, Dhaka, Bangladesh
| | - Arun Kumar
- Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India
| | - Sandeep Arora
- Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India
| | - Rokeya Akter
- Department of Global Medical Science, Wonju College of Medicine, Yonsei University, Seoul, South Korea
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