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Nandakumar R, Shi X, Gu H, Kim Y, Raskind WH, Peter B, Dinu V. Joint exome and metabolome analysis in individuals with dyslexia: Evidence for associated dysregulations of olfactory perception and autoimmune functions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.600448. [PMID: 39005457 PMCID: PMC11244894 DOI: 10.1101/2024.06.27.600448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Dyslexia is a learning disability that negatively affects reading, writing, and spelling development at the word level in 5%-9% of children. The phenotype is variable and complex, involving several potential cognitive and physical concomitants such as sensory dysregulation and immunodeficiencies. The biological pathogenesis is not well-understood. Toward a better understanding of the biological drivers of dyslexia, we conducted the first joint exome and metabolome investigation in a pilot sample of 30 participants with dyslexia and 13 controls. In this analysis, eight metabolites of interest emerged (pyridoxine, kynurenic acid, citraconic acid, phosphocreatine, hippuric acid, xylitol, 2-deoxyuridine, and acetylcysteine). A metabolite-metabolite interaction analysis identified Krebs cycle intermediates that may be implicated in the development of dyslexia. Gene ontology analysis based on exome variants resulted in several pathways of interest, including the sensory perception of smell (olfactory) and immune system-related responses. In the joint exome and metabolite analysis, the olfactory transduction pathway emerged as the primary pathway of interest. Although the olfactory transduction and Krebs cycle pathways have not previously been described in dyslexia literature, these pathways have been implicated in other neurodevelopmental disorders including autism spectrum disorder and obsessive-compulsive disorder, suggesting the possibility of these pathways playing a role in dyslexia as well. Immune system response pathways, on the other hand, have been implicated in both dyslexia and other neurodevelopmental disorders.
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2
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Duan R, Tong X. Electrophysiological markers of orthographic pattern learning in school-aged children with reading challenges: An ERP investigation. RESEARCH IN DEVELOPMENTAL DISABILITIES 2024; 151:104784. [PMID: 38941692 DOI: 10.1016/j.ridd.2024.104784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/14/2024] [Accepted: 06/16/2024] [Indexed: 06/30/2024]
Abstract
BACKGROUND Previous studies suggested that children with reading difficulty have impaired statistical learning ability in extracting distributional orthographic regularities. However, the neural mechanisms underlying have not been fully investigated. AIMS The current study aimed to identify the electrophysiological markers and to examine the neural underpinnings of statistical learning of orthographic regularities in children with reading difficulties. METHODS AND PROCEDURES Using the event-related potentials (ERPs) and the orthographic learning task, 157 children were exposed to a sequence of artificial pseudocharacters with varying levels of positional and semantic consistency (low at 60 %, moderate at 80 %, and high at 100 %). OUTCOMES AND RESULTS Poor readers elicited an increased N170 response in the low consistency and a lack of left-lateralized P300 effect when learning positional regularities of radicals. Similarly, larger N170 effects were observed in poor readers, while similar N400 effects were found in both poor and average readers when learning semantic regularities of radicals. CONCLUSIONS AND IMPLICATIONS Our findings indicate that poor readers may have trouble using statistical information for early-stage orthographic pattern extraction, yet they can identify semantic inconsistencies after sufficient exposure. These results deepen our understanding of the neural mechanisms involved in statistical learning for poor readers and aid in improving criteria for differentiating between typically developing children and those with reading challenges.
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Affiliation(s)
- Rujun Duan
- Department of Psychology, The Education University of Hong Kong, Hong Kong
| | - Xiuhong Tong
- Department of Psychology, The Education University of Hong Kong, Hong Kong.
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Bonte M, Brem S. Unraveling individual differences in learning potential: A dynamic framework for the case of reading development. Dev Cogn Neurosci 2024; 66:101362. [PMID: 38447471 PMCID: PMC10925938 DOI: 10.1016/j.dcn.2024.101362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 02/02/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024] Open
Abstract
Children show an enormous capacity to learn during development, but with large individual differences in the time course and trajectory of learning and the achieved skill level. Recent progress in developmental sciences has shown the contribution of a multitude of factors including genetic variation, brain plasticity, socio-cultural context and learning experiences to individual development. These factors interact in a complex manner, producing children's idiosyncratic and heterogeneous learning paths. Despite an increasing recognition of these intricate dynamics, current research on the development of culturally acquired skills such as reading still has a typical focus on snapshots of children's performance at discrete points in time. Here we argue that this 'static' approach is often insufficient and limits advancements in the prediction and mechanistic understanding of individual differences in learning capacity. We present a dynamic framework which highlights the importance of capturing short-term trajectories during learning across multiple stages and processes as a proxy for long-term development on the example of reading. This framework will help explain relevant variability in children's learning paths and outcomes and fosters new perspectives and approaches to study how children develop and learn.
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Affiliation(s)
- Milene Bonte
- Department of Cognitive Neuroscience and Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland; URPP Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, Zurich, Switzerland
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4
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Panahi R, Akbari M, Jarollahi F, Haghani H, Kazemnezhad Leyli E, Zia M. Atypical function of auditory sensory gating in children with developmental dyslexia: Investigating its relationship with cognitive abilities. DYSLEXIA (CHICHESTER, ENGLAND) 2023; 29:426-440. [PMID: 37779260 DOI: 10.1002/dys.1754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 06/24/2023] [Accepted: 09/12/2023] [Indexed: 10/03/2023]
Abstract
Impairments of auditory processing are among frequent findings in dyslexia. However, it is unclear how auditory signals are gated from brainstem to higher central processing stages in these individuals. The present study was done to investigate auditory sensory gating in children with developmental dyslexia (DD), and to determine whether sensory gating correlates with performance on behavioural tasks. Auditory sensory gating at P50, N1 and P2 waves was evaluated in two groups including 20 children with DD and 19 children with typical reading development (TRD). Behavioural tests were used to evaluate phonological working memory (PWM) and selective attention abilities. Sensory gating in children with DD was significantly less efficient than their peers at P50, N1 and P2 waves. Lower auditory evoked potential (AEP) amplitudes were found in the DD group. The children with TRD scored better in all the behavioural tests. Relationships were reported between sensory gating at P50, N1, P2 and behavioural performance in the two groups. Children with dyslexia had deficient sensory gating in comparison with controls. In addition, children with dyslexia experienced problems with PWM and selective attention tasks. The function of sensory gating was associated with attentional and PWM performances in this group.
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Affiliation(s)
- Rasool Panahi
- Otorhinolaryngology Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
- Department of Audiology, School of Rehabilitation Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Mehdi Akbari
- Department of Audiology, School of Rehabilitation Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Farnoush Jarollahi
- Department of Audiology, School of Rehabilitation Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Hamid Haghani
- Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Ehsan Kazemnezhad Leyli
- Department of Biostatistics, Guilan Road Trauma Research Center, Guilan University of Medical Sciences, Rasht, Iran
| | - Maryam Zia
- Otorhinolaryngology Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
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Peter B, Bruce L, Finestack L, Dinu V, Wilson M, Klein-Seetharaman J, Lewis CR, Braden BB, Tang YY, Scherer N, VanDam M, Potter N. Precision Medicine as a New Frontier in Speech-Language Pathology: How Applying Insights From Behavior Genomics Can Improve Outcomes in Communication Disorders. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2023; 32:1397-1412. [PMID: 37146603 PMCID: PMC10484627 DOI: 10.1044/2023_ajslp-22-00205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/07/2022] [Accepted: 03/01/2023] [Indexed: 05/07/2023]
Abstract
PURPOSE Precision medicine is an emerging intervention paradigm that leverages knowledge of risk factors such as genotypes, lifestyle, and environment toward proactive and personalized interventions. Regarding genetic risk factors, examples of interventions informed by the field of medical genomics are pharmacological interventions tailored to an individual's genotype and anticipatory guidance for children whose hearing impairment is predicted to be progressive. Here, we show how principles of precision medicine and insights from behavior genomics have relevance for novel management strategies of behaviorally expressed disorders, especially disorders of spoken language. METHOD This tutorial presents an overview of precision medicine, medical genomics, and behavior genomics; case examples of improved outcomes; and strategic goals toward enhancing clinical practice. RESULTS Speech-language pathologists (SLPs) see individuals with various communication disorders due to genetic variants. Ways of using insights from behavior genomics and implementing principles of precision medicine include recognizing early signs of undiagnosed genetic disorders in an individual's communication patterns, making appropriate referrals to genetics professionals, and incorporating genetic findings into management plans. Patients benefit from a genetics diagnosis by gaining a deeper and more prognostic understanding of their condition, obtaining more precisely targeted interventions, and learning about their recurrence risks. CONCLUSIONS SLPs can achieve improved outcomes by expanding their purview to include genetics. To drive this new interdisciplinary framework forward, goals should include systematic training in clinical genetics for SLPs, enhanced understanding of genotype-phenotype associations, leveraging insights from animal models, optimizing interprofessional team efforts, and developing novel proactive and personalized interventions.
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Affiliation(s)
- Beate Peter
- College of Health Solutions, Arizona State University, Tempe
| | - Laurel Bruce
- College of Health Solutions, Arizona State University, Tempe
| | - Lizbeth Finestack
- Department of Speech-Language-Hearing Sciences, University of Minnesota, Twin Cities, Minneapolis
| | - Valentin Dinu
- College of Health Solutions, Arizona State University, Tempe
| | - Melissa Wilson
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe
| | | | - Candace R. Lewis
- School of Life Sciences, Arizona State University, Tempe
- Department of Psychology, Arizona State University, Tempe
| | - B. Blair Braden
- College of Health Solutions, Arizona State University, Tempe
| | - Yi-Yuan Tang
- College of Health Solutions, Arizona State University, Tempe
| | - Nancy Scherer
- College of Health Solutions, Arizona State University, Tempe
| | - Mark VanDam
- Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, Spokane
| | - Nancy Potter
- Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, Spokane
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Carrion J, Nandakumar R, Shi X, Gu H, Kim Y, Raskind WH, Peter B, Dinu V. A data-fusion approach to identifying developmental dyslexia from multi-omics datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.27.530280. [PMID: 36909570 PMCID: PMC10002702 DOI: 10.1101/2023.02.27.530280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
This exploratory study tested and validated the use of data fusion and machine learning techniques to probe high-throughput omics and clinical data with a goal of exploring the etiology of developmental dyslexia. Developmental dyslexia is the leading learning disability in school aged children affecting roughly 5-10% of the US population. The complex biological and neurological phenotype of this life altering disability complicates its diagnosis. Phenome, exome, and metabolome data was collected allowing us to fully explore this system from a behavioral, cellular, and molecular point of view. This study provides a proof of concept showing that data fusion and ensemble learning techniques can outperform traditional machine learning techniques when provided small and complex multi-omics and clinical datasets. Heterogenous stacking classifiers consisting of single-omic experts/models achieved an accuracy of 86%, F1 score of 0.89, and AUC value of 0.83. Ensemble methods also provided a ranked list of important features that suggests exome single nucleotide polymorphisms found in the thalamus and cerebellum could be potential biomarkers for developmental dyslexia and heavily influenced the classification of DD within our machine learning models.
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Affiliation(s)
- Jackson Carrion
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
| | - Rohit Nandakumar
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
| | - Xiaojian Shi
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
- Cellular and Molecular Physiology Department, Yale School of Medicine, New Haven, CT 06510
| | - Haiwei Gu
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
- Center for Translational Science, Florida International University, Port St. Lucie, FL 34987
| | - Yookyung Kim
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
| | - Wendy H Raskind
- Department of Medicine/Medical Genetics, University of Washington, Seattle, WA 98105
| | - Beate Peter
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
| | - Valentin Dinu
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004
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Campbell J, Rouse R, Nielsen M, Potter S. Sensory Inhibition and Speech Perception-in-Noise Performance in Children With Normal Hearing. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2023; 66:382-399. [PMID: 36480698 DOI: 10.1044/2022_jslhr-22-00077] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
PURPOSE This study investigated whether sensory inhibition in children may be associated with speech perception-in-noise performance. Additionally, gating networks associated with sensory inhibition were identified via standardized low-resolution brain electromagnetic tomography (sLORETA), and the detectability of the cortical auditory evoked potential (CAEP) N1 response was enhanced using a 4- to 30-Hz bandpass filter. METHOD CAEP gating responses, reflective of inhibition, were evoked via click pairs and recorded using high-density electroencephalography in neurotypical 5- to 8-year-olds and 22- to 24-year-olds. Amplitude gating indices were calculated and correlated with speech perception in noise. Gating generators were estimated using sLORETA. A 4- to 30-Hz filter was applied to detect the N1 gating component. RESULTS Preliminary findings indicate children showed reduced gating, but there was a correlational trend between better speech perception and decreased N2 gating. Commensurate with decreased gating, children presented with incomplete compensatory gating networks. The 4- to 30-Hz filter identified the N1 response in a subset of children. CONCLUSIONS There was a tenuous relationship between children's speech perception and sensory inhibition. This may suggest that sensory inhibition is only implicated in atypically poor speech perception. Finally, the 4- to 30-Hz filter settings are critical in N1 detectability. SIGNIFICANCE Gating may help evaluate reduced sensory inhibition in children with clinically poor speech perception using the appropriate methodology. Cortical gating generators in typically developing children are also newly identified.
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Affiliation(s)
- Julia Campbell
- Central Sensory Processes Laboratory, Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin
| | - Rixon Rouse
- Central Sensory Processes Laboratory, Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin
| | - Mashhood Nielsen
- Central Sensory Processes Laboratory, Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin
| | - Sheri Potter
- Central Sensory Processes Laboratory, Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin
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8
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Tong SX, Duan R, Shen W, Yu Y, Tong X. Multiple mechanisms regulate statistical learning of orthographic regularities in school-age children: Neurophysiological evidence. Dev Cogn Neurosci 2022; 59:101190. [PMID: 36549147 PMCID: PMC9795533 DOI: 10.1016/j.dcn.2022.101190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 11/15/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
Using event-related potentials (ERPs), this study investigated how the brains of Chinese children of different ages extract and encode relational patterns contained in orthographic input. Ninety-nine Chinese children in Grades 1-3 performed an artificial orthography statistical learning task that comprised logographic components embedded in characters with high (100%), moderate (80%), and low (60%) positional consistency. The behavioral results indicated that across grades, participants more accurately recognized characters with high rather than low consistency. The neurophysiological results revealed that in each grade, the amplitude of some ERP components differed, with a larger P1 effect in the high consistency condition and a larger N170 and left-lateralized P300 effect in the low consistency condition. A smaller N170 effect occurred in Grade 3 than in Grade 1, and a larger P300 effect occurred in Grade 1 than in either Grade 2 or 3. These findings suggest the dynamic nature of statistical learning by showing that neural adaptation associated with N170, and attention and working memory related to P1 and P300, regulate different types of structural input, and that children's abilities to prioritize these mechanisms vary with context and age.
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Affiliation(s)
- Shelley Xiuli Tong
- Human Communication, Development, and Information Sciences, Faculty of Education, The University of Hong Kong, Hong Kong SAR, China
| | - Rujun Duan
- Department of Psychology, The Education University of Hong Kong, Hong Kong SAR, China
| | - Wei Shen
- Institute of Psychological Sciences, Hangzhou Normal University, China
| | - Yilin Yu
- School of Foreign Languages, Anyang Normal University, China
| | - Xiuhong Tong
- Department of Psychology, The Education University of Hong Kong, Hong Kong SAR, China,Correspondence to: Department of Psychology, The Education University of Hong Kong, 10 Lo Ping Road, Tai Po, New Territories, Hong Kong, China.
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9
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Beach SD, Ozernov-Palchik O, May SC, Centanni TM, Perrachione TK, Pantazis D, Gabrieli JDE. The Neural Representation of a Repeated Standard Stimulus in Dyslexia. Front Hum Neurosci 2022; 16:823627. [PMID: 35634200 PMCID: PMC9133793 DOI: 10.3389/fnhum.2022.823627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
The neural representation of a repeated stimulus is the standard against which a deviant stimulus is measured in the brain, giving rise to the well-known mismatch response. It has been suggested that individuals with dyslexia have poor implicit memory for recently repeated stimuli, such as the train of standards in an oddball paradigm. Here, we examined how the neural representation of a standard emerges over repetitions, asking whether there is less sensitivity to repetition and/or less accrual of "standardness" over successive repetitions in dyslexia. We recorded magnetoencephalography (MEG) as adults with and without dyslexia were passively exposed to speech syllables in a roving-oddball design. We performed time-resolved multivariate decoding of the MEG sensor data to identify the neural signature of standard vs. deviant trials, independent of stimulus differences. This "multivariate mismatch" was equally robust and had a similar time course in the two groups. In both groups, standards generated by as few as two repetitions were distinct from deviants, indicating normal sensitivity to repetition in dyslexia. However, only in the control group did standards become increasingly different from deviants with repetition. These results suggest that many of the mechanisms that give rise to neural adaptation as well as mismatch responses are intact in dyslexia, with the possible exception of a putatively predictive mechanism that successively integrates recent sensory information into feedforward processing.
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Affiliation(s)
- Sara D. Beach
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA, United States
| | - Ola Ozernov-Palchik
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Sidney C. May
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Tracy M. Centanni
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Tyler K. Perrachione
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA, United States
- Department of Speech, Language and Hearing Sciences, Boston University, Boston, MA, United States
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - John D. E. Gabrieli
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA, United States
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10
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Beach SD, Lim SJ, Cardenas-Iniguez C, Eddy MD, Gabrieli JDE, Perrachione TK. Electrophysiological correlates of perceptual prediction error are attenuated in dyslexia. Neuropsychologia 2022; 165:108091. [PMID: 34801517 PMCID: PMC8807066 DOI: 10.1016/j.neuropsychologia.2021.108091] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/09/2021] [Accepted: 11/17/2021] [Indexed: 01/30/2023]
Abstract
A perceptual adaptation deficit often accompanies reading difficulty in dyslexia, manifesting in poor perceptual learning of consistent stimuli and reduced neurophysiological adaptation to stimulus repetition. However, it is not known how adaptation deficits relate to differences in feedforward or feedback processes in the brain. Here we used electroencephalography (EEG) to interrogate the feedforward and feedback contributions to neural adaptation as adults with and without dyslexia viewed pairs of faces and words in a paradigm that manipulated whether there was a high probability of stimulus repetition versus a high probability of stimulus change. We measured three neural dependent variables: expectation (the difference between prestimulus EEG power with and without the expectation of stimulus repetition), feedforward repetition (the difference between event-related potentials (ERPs) evoked by an expected change and an unexpected repetition), and feedback-mediated prediction error (the difference between ERPs evoked by an unexpected change and an expected repetition). Expectation significantly modulated prestimulus theta- and alpha-band EEG in both groups. Unexpected repetitions of words, but not faces, also led to significant feedforward repetition effects in the ERPs of both groups. However, neural prediction error when an unexpected change occurred instead of an expected repetition was significantly weaker in dyslexia than the control group for both faces and words. These results suggest that the neural and perceptual adaptation deficits observed in dyslexia reflect the failure to effectively integrate perceptual predictions with feedforward sensory processing. In addition to reducing perceptual efficiency, the attenuation of neural prediction error signals would also be deleterious to the wide range of perceptual and procedural learning abilities that are critical for developing accurate and fluent reading skills.
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Affiliation(s)
- Sara D. Beach
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A.,Program in Speech and Hearing Bioscience and Technology, Harvard University, 260 Longwood Avenue, Boston, MA 02115 U.S.A
| | - Sung-Joo Lim
- Department of Speech, Language, and Hearing Sciences, Boston University, 635 Commonwealth Avenue, Boston, MA 02215 U.S.A
| | - Carlos Cardenas-Iniguez
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A
| | - Marianna D. Eddy
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A
| | - John D. E. Gabrieli
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A
| | - Tyler K. Perrachione
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 U.S.A.,Department of Speech, Language, and Hearing Sciences, Boston University, 635 Commonwealth Avenue, Boston, MA 02215 U.S.A.,Correspondence: Tyler K. Perrachione, Ph.D., Department of Speech, Language, and Hearing Sciences, Boston University, 635 Commonwealth Ave., Boston, MA 02215, Phone: +1.617.358.7410,
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11
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Wang C, Wang Z, Xie B, Shi X, Yang P, Liu L, Qu T, Qin Q, Xing Y, Zhu W, Teipel SJ, Jia J, Zhao G, Li L, Tang Y. Binaural processing deficit and cognitive impairment in Alzheimer's disease. Alzheimers Dement 2021; 18:1085-1099. [PMID: 34569690 DOI: 10.1002/alz.12464] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/07/2021] [Accepted: 08/05/2021] [Indexed: 01/08/2023]
Abstract
Speech comprehension in noisy environments depends on central auditory functions, which are vulnerable in Alzheimer's disease (AD). Binaural processing exploits two ear sounds to optimally process degraded sound information; its characteristics are poorly understood in AD. We studied behavioral and electrophysiological alterations in binaural processing among 121 participants (AD = 27; amnestic mild cognitive impairment [aMCI] = 33; subjective cognitive decline [SCD] = 30; cognitively normal [CN] = 31). We observed impairment of binaural processing in AD and aMCI, and detected a U-shaped curve change in phase synchrony (declining from CN to SCD and to aMCI, but increasing from aMCI to AD). This improvement in phase synchrony accompanying more severe cognitive stages could reflect neural adaptation for binaural processing. Moreover, increased phase synchrony is associated with worse memory during the stages when neural adaptation apparently occurs. These findings support a hypothesis that neural adaptation for binaural processing deficit may exacerbate cognitive impairment, which could help identify biomarkers and therapeutic targets in AD.
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Affiliation(s)
- Changming Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Zhibin Wang
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Beijia Xie
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Xinrui Shi
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Pengcheng Yang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China.,Speech and Hearing Research Center, Peking University, Beijing, China
| | - Lei Liu
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China.,Speech and Hearing Research Center, Peking University, Beijing, China
| | - Tianshu Qu
- Speech and Hearing Research Center, Peking University, Beijing, China.,Key Laboratory on Machine Perception (Ministry of Education), Peking University, Beijing, China
| | - Qi Qin
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Yi Xing
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China.,Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China
| | - Wei Zhu
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Stefan J Teipel
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany.,DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany
| | - Jianping Jia
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China.,Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Liang Li
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China.,Speech and Hearing Research Center, Peking University, Beijing, China.,Key Laboratory on Machine Perception (Ministry of Education), Peking University, Beijing, China.,Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.,Beijing Institute for Brain Disorders, Beijing, China
| | - Yi Tang
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China.,Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China
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Zhang M, Riecke L, Bonte M. Neurophysiological tracking of speech-structure learning in typical and dyslexic readers. Neuropsychologia 2021; 158:107889. [PMID: 33991561 DOI: 10.1016/j.neuropsychologia.2021.107889] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 05/03/2021] [Accepted: 05/10/2021] [Indexed: 10/21/2022]
Abstract
Statistical learning, or the ability to extract statistical regularities from the sensory environment, plays a critical role in language acquisition and reading development. Here we employed electroencephalography (EEG) with frequency-tagging measures to track the temporal evolution of speech-structure learning in individuals with reading difficulties due to developmental dyslexia and in typical readers. We measured EEG while participants listened to (a) a structured stream of repeated tri-syllabic pseudowords, (b) a random stream of the same isochronous syllables, and (c) a series of tri-syllabic real Dutch words. Participants' behavioral learning outcome (pseudoword recognition) was measured after training. We found that syllable-rate tracking was comparable between the two groups and stable across both the random and structured streams of syllables. More importantly, we observed a gradual emergence of the tracking of tri-syllabic pseudoword structures in both groups. Compared to the typical readers, however, in the dyslexic readers this implicit speech structure learning seemed to build up at a slower pace. A brain-behavioral correlation analysis showed that slower learners (i.e., participants who were slower in establishing the neural tracking of pseudowords) were less skilled in phonological awareness. Moreover, those who showed stronger neural tracking of real words tended to be less fluent in the visual-verbal conversion of linguistic symbols. Taken together, our study provides an online neurophysiological approach to track the progression of implicit learning processes and gives insights into the learning difficulties associated with dyslexia from a dynamic perspective.
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Affiliation(s)
- Manli Zhang
- Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Lars Riecke
- Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Milene Bonte
- Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Peter B, Albert A, Panagiotides H, Gray S. Sequential and spatial letter reversals in adults with dyslexia during a word comparison task: demystifying the "was saw" and "db" myths. CLINICAL LINGUISTICS & PHONETICS 2021; 35:340-367. [PMID: 31959003 DOI: 10.1080/02699206.2019.1705916] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Revised: 12/10/2019] [Accepted: 12/13/2019] [Indexed: 06/10/2023]
Abstract
Whether sequential and spatial letter reversals characterize dyslexia in children has been unclear, largely due to developmental variability of these errors in children with and without dyslexia. Here we demonstrate both types of reversals for the first time in adults with dyslexia (n = 22) but not in control adults (n = 20). Participants evaluated 576 word pairs that consisted of two identical words or two words that differed subtly, by categorizing them as same or different. Two subsets of word pairs differed in sequential (e.g. "two tow") and spatial (e.g. "cob cod") letter reversals. The adults with dyslexia were less accurate than the controls regarding both types of word pairs. Their accuracy during left/right letter reversals was lower, compared to both up/down letter reversals (e.g. "cub cup") and nonsymmetric letter similarities (e.g. "half halt"). Accuracy during left/right reversals was correlated with accuracy during sequential rearrangement in the word pair task as well as with a composite measure of sequential processing based on nonword repetition, nonword reading, and multisyllabic word repetition. It was also correlated with a composite measure of literacy skills. A subset of the dyslexia group who produced left/right errors during a rapid single letter naming task obtained lower accuracy than the dyslexia subgroup without such errors during both types of letter reversals, and their overall literacy skills were lower. We conclude that sequential and left/right letter reversals characterize a severe dyslexia subtype. These two types of reversal are associated, are part of a general deficit in sequential processing likely due to cerebellar deficits, and persist into adulthood.
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Affiliation(s)
- Beate Peter
- Speech and Hearing Science, College of Health Solutions, Arizona State University, Tempe, Arizona, USA
- Department of Communication Sciences and Disorders, Saint Louis University, Saint Louis, Missouri, USA
| | - Andria Albert
- Speech and Hearing Science, College of Health Solutions, Arizona State University, Tempe, Arizona, USA
| | - Heracles Panagiotides
- Jackson School of International Studies, University of Washington, Seattle, Washington, USA
| | - Shelley Gray
- Speech and Hearing Science, College of Health Solutions, Arizona State University, Tempe, Arizona, USA
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Peter B, Albert A, Gray S. Spelling errors reveal underlying sequential and spatial processing deficits in adults with dyslexia. CLINICAL LINGUISTICS & PHONETICS 2021; 35:310-339. [PMID: 32552235 DOI: 10.1080/02699206.2020.1780322] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 06/03/2020] [Accepted: 06/05/2020] [Indexed: 06/11/2023]
Abstract
Recent studies showed that some adults with dyslexia have difficulty processing sequentially arranged information. In a companion study, this deficit manifested as low accuracy during a word pair comparison task involving same/different decisions when two words differed in their letter sequences. This sequential deficit was associated with left/right spatial letter confusion. In the present study, we found the same underlying difficulty with sequential and spatial letter processing during word spelling. Participants were the same 22 adults with dyslexia and 20 age- and gender-matched controls as in the companion study. In the spelling task, sequential error rates were higher in the dyslexia group, compared to the controls. Measures of accuracy of serial letter order during the spelling task and the word comparison task were correlated. Only three participants, each with dyslexia, produced left/right letter reversals during spelling. These were the same participants who produced left/right errors when naming single letters. They also had profound difficulty with sequential and left/right letter processing in the spelling and word comparison tasks, and they had the most severe spelling impairment. We conclude that this pervasive, persistent difficulty with sequential and spatial reversals contributes to a severe dyslexia subtype. In the dyslexia group as a whole, additional and separate sources of errors were underspecified word representations in long-term memory and homophone errors that likely represent language-based deficits in word knowledge. In the participants, these three factors (sequential/spatial letter confusion, underspecified word form representation, language-based deficits) occurred either as single factors or in combination with each other.
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Affiliation(s)
- Beate Peter
- Speech and Hearing Science, College of Health Solutions, Arizona State University, Tempe, AZ, USA
- Department of Communication Sciences and Disorders, Saint Louis University, Saint Louis, MO, USA
| | - Andria Albert
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Shelley Gray
- Speech and Hearing Science, College of Health Solutions, Arizona State University, Tempe, AZ, USA
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Wang S, Wang T, Chen N, Luo J. The preconditions and event-related potentials correlates of flow experience in an educational context. LEARNING AND MOTIVATION 2020. [DOI: 10.1016/j.lmot.2020.101678] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Williams NS, McArthur GM, de Wit B, Ibrahim G, Badcock NA. A validation of Emotiv EPOC Flex saline for EEG and ERP research. PeerJ 2020; 8:e9713. [PMID: 32864218 PMCID: PMC7427545 DOI: 10.7717/peerj.9713] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 07/23/2020] [Indexed: 01/23/2023] Open
Abstract
Background Previous work has validated consumer-grade electroencephalography (EEG) systems for use in research. Systems in this class are cost-effective and easy to set up and can facilitate neuroscience outside of the laboratory. The aim of the current study was to determine if a new consumer-grade system, the Emotiv EPOC Saline Flex, was capable of capturing research-quality data. Method The Emotiv system was used simultaneously with a research-grade EEG system, Neuroscan Synamps2, to collect EEG data across 16 channels during five well-established paradigms: (1) a mismatch negativity (MMN) paradigm that involved a passive listening task in which rare deviant (1,500 Hz) tones were interspersed amongst frequent standard tones (1,000 Hz), with instructions to ignore the tones while watching a silent movie; (2) a P300 paradigm that involved an active listening task in which participants were asked to count rare deviant tones presented amongst frequent standard tones; (3) an N170 paradigm in which participants were shown images of faces and watches and asked to indicate whether the images were upright or inverted; (4) a steady-state visual evoked potential (SSVEP) paradigm in which participants passively viewed a flickering screen (15 Hz) for 2 min; and (5) a resting state paradigm in which participants sat quietly with their eyes open and then closed for 3 min each. Results The MMN components and P300 peaks were equivalent between the two systems (BF10 = 0.25 and BF10 = 0.26, respectively), with high intraclass correlations (ICCs) between the ERP waveforms (>0.81). Although the N170 peak values recorded by the two systems were different (BF10 = 35.88), ICCs demonstrated that the N170 ERP waveforms were strongly correlated over the right hemisphere (P8; 0.87–0.97), and moderately-to-strongly correlated over the left hemisphere (P7; 0.52–0.84). For the SSVEP, the signal-to-noise ratio (SNR) was larger for Neuroscan than Emotiv EPOC Flex (19.94 vs. 8.98, BF10 = 51,764), but SNR z-scores indicated a significant brain response at the stimulus frequency for both Neuroscan (z = 12.47) and Flex (z = 11.22). In the resting state task, both systems measured similar alpha power (BF10 = 0.28) and higher alpha power when the eyes were closed than open (BF10 = 32.27). Conclusions The saline version of the Emotiv EPOC Flex captures data similar to that of a research-grade EEG system. It can be used to measure reliable auditory and visual research-quality ERPs. In addition, it can index SSVEP signatures and is sensitive to changes in alpha oscillations.
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Affiliation(s)
- Nikolas S Williams
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | | | - Bianca de Wit
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - George Ibrahim
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Nicholas A Badcock
- Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia.,School of Psychological Science, University of Western Australia, Perth, WA, Australia
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Implicit learning in the developing brain: An exploration of ERP indices for developmental disorders. Clin Neurophysiol 2019; 130:2166-2168. [PMID: 31542253 DOI: 10.1016/j.clinph.2019.09.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 08/27/2019] [Accepted: 09/01/2019] [Indexed: 11/20/2022]
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