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Li M, Izumoto M, Wang Y, Kato Y, Iwatani Y, Hirata I, Mizuno Y, Tachibana M, Mohri I, Kagitani-Shimono K. Altered white matter connectivity of ventral language networks in autism spectrum disorder: An automated fiber quantification analysis with multi-site datasets. Neuroimage 2024; 297:120731. [PMID: 39002786 DOI: 10.1016/j.neuroimage.2024.120731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 06/28/2024] [Accepted: 07/11/2024] [Indexed: 07/15/2024] Open
Abstract
Comprehension and pragmatic deficits are prevalent in autism spectrum disorder (ASD) and are potentially linked to altered connectivity in the ventral language networks. However, previous magnetic resonance imaging studies have not sufficiently explored the microstructural abnormalities in the ventral fiber tracts underlying comprehension dysfunction in ASD. Additionally, the precise locations of white matter (WM) changes in the long tracts of patients with ASD remain poorly understood. In the current study, we applied the automated fiber-tract quantification (AFQ) method to investigate the fine-grained WM properties of the ventral language pathway and their relationships with comprehension and symptom manifestation in ASD. The analysis included diffusion/T1 weighted imaging data of 83 individuals with ASD and 83 age-matched typically developing (TD) controls. Case-control comparisons were performed on the diffusion metrics of the ventral tracts at both the global and point-wise levels. We also explored correlations between diffusion metrics, comprehension performance, and ASD traits, and conducted subgroup analyses based on age range to examine developmental moderating effects. Individuals with ASD exhibited remarkable hypoconnectivity in the ventral tracts, particularly in the temporal portions of the left inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF). These WM abnormalities were associated with poor comprehension and more severe ASD symptoms. Furthermore, WM alterations in the ventral tract and their correlation with comprehension dysfunction were more prominent in younger children with ASD than in adolescents. These findings indicate that WM disruptions in the temporal portions of the left ILF/IFOF are most notable in ASD, potentially constituting the core neurological underpinnings of comprehension and communication deficits in autism. Moreover, impaired WM connectivity and comprehension ability in patients with ASD appear to improve with age.
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Affiliation(s)
- Min Li
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Maya Izumoto
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yide Wang
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoko Kato
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoshiko Iwatani
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Ikuko Hirata
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoshifumi Mizuno
- Research Center for Child Mental Development, University of Fukui, Fukui, Japan
| | - Masaya Tachibana
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Ikuko Mohri
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Kuriko Kagitani-Shimono
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan.
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2
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Alho J, Samuelsson JG, Khan S, Mamashli F, Bharadwaj H, Losh A, McGuiggan NM, Graham S, Nayal Z, Perrachione TK, Joseph RM, Stoodley CJ, Hämäläinen MS, Kenet T. Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder. Hum Brain Mapp 2023; 44:5810-5827. [PMID: 37688547 PMCID: PMC10619366 DOI: 10.1002/hbm.26478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 08/11/2023] [Accepted: 08/20/2023] [Indexed: 09/11/2023] Open
Abstract
Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI.
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Affiliation(s)
- Jussi Alho
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - John G. Samuelsson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Harvard‐MIT Division of Health Sciences and Technology, Massachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Sheraz Khan
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fahimeh Mamashli
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Hari Bharadwaj
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Speech, Language, and Hearing Sciences, and Weldon School of Biomedical EngineeringPurdue UniversityWest LafayetteIndianaUSA
| | - Ainsley Losh
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nicole M. McGuiggan
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Steven Graham
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Zein Nayal
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Tyler K. Perrachione
- Department of Speech, Language, and Hearing SciencesBoston UniversityBostonMassachusettsUSA
| | - Robert M. Joseph
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
| | - Catherine J. Stoodley
- Department of PsychologyCollege of Arts and Sciences, American UniversityWashingtonDCUSA
| | - Matti S. Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Tal Kenet
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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3
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So WC, Song XK. Whose Gestures are More Predictive of Expressive Language Abilities among Chinese-Speaking Children with Autism? A Comparison of Caregivers' and Children's Gestures. J Autism Dev Disord 2023; 53:3449-3459. [PMID: 35781854 DOI: 10.1007/s10803-022-05658-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/16/2022] [Indexed: 11/28/2022]
Abstract
In spite of the close relationship between gestures and expressive language, little research has examined the roles of the parents' and children's gestures in the development of expressive language abilities in autistic children. Previous findings are also inconclusive. In the present study, we coded the gestures produced by the parents and their autistic children in parent-child interactions and compared the influence of their gestures on the children's expressive language abilities (N = 35; M = 4;10). Autistic children's deictic gestures positively predicted their Mean Length Utterance (MLU), word types, and word tokens whereas parents' deictic gesture inputs negatively predicted MLU and word types. The findings shed light on the importance of the gestures made by autistic children, which may trigger parents' gesture-to-word translation.
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Affiliation(s)
- Wing-Chee So
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong.
| | - Xue-Ke Song
- Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
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Li M, Wang Y, Tachibana M, Rahman S, Kagitani-Shimono K. Atypical structural connectivity of language networks in autism spectrum disorder: A meta-analysis of diffusion tensor imaging studies. Autism Res 2022; 15:1585-1602. [PMID: 35962721 PMCID: PMC9546367 DOI: 10.1002/aur.2789] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 07/25/2022] [Indexed: 11/20/2022]
Abstract
Patients with autism spectrum disorder (ASD) often show pervasive and complex language impairments that are closely associated with aberrant structural connectivity of language networks. However, the characteristics of white matter connectivity in ASD have remained inconclusive in previous diffusion tensor imaging (DTI) studies. The current meta‐analysis aimed to comprehensively elucidate the abnormality in language‐related white matter connectivity in individuals with ASD. We searched PubMed, Web of Science, Scopus, and Medline databases to identify relevant studies. The standardized mean difference was calculated to measure the pooled difference in DTI metrics in each tract between the ASD and typically developing (TD) groups. The moderating effects of age, sex, language ability, and symptom severity were investigated using subgroup and meta‐regression analysis. Thirty‐three DTI studies involving 831 individuals with ASD and 836 TD controls were included in the meta‐analysis. ASD subjects showed significantly lower fractional anisotropy or higher mean diffusivity across language‐associated tracts than TD controls. These abnormalities tended to be more prominent in the left language networks than in the right. In addition, children with ASD exhibit more pronounced and pervasive disturbances in white matter connectivity than adults. These results support the under‐connectivity hypothesis and demonstrate the widespread abnormal microstructure of language‐related tracts in patients with ASD. Otherwise, white matter abnormalities in the autistic brain could vary depending on the developmental stage and hemisphere.
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Affiliation(s)
- Min Li
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
| | - Yide Wang
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
| | - Masaya Tachibana
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
| | - Shafiur Rahman
- Department of Child Development, United Graduate School of Child Development, Hamamatsu University School of Medicine, Higashi-ku, Hamamatsu, Shizuoka, Japan.,Research Center for Child Mental Development, Hamamatsu University School of Medicine, Higashi-ku, Hamamatsu, Shizuoka, Japan
| | - Kuriko Kagitani-Shimono
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
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Heller Murray ES, Segawa J, Karahanoglu FI, Tocci C, Tourville JA, Nieto-Castanon A, Tager-Flusberg H, Manoach DS, Guenther FH. Increased Intra-Subject Variability of Neural Activity During Speech Production in People with Autism Spectrum Disorder. RESEARCH IN AUTISM SPECTRUM DISORDERS 2022; 94:101955. [PMID: 35601992 PMCID: PMC9119427 DOI: 10.1016/j.rasd.2022.101955] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Background Communication difficulties are a core deficit in many people with autism spectrum disorder (ASD). The current study evaluated neural activation in participants with ASD and neurotypical (NT) controls during a speech production task. Methods Neural activities of participants with ASD (N = 15, M = 16.7 years, language abilities ranged from low verbal abilities to verbally fluent) and NT controls (N = 12, M = 17.1 years) was examined using functional magnetic resonance imaging with a sparse-sampling paradigm. Results There were no differences between the ASD and NT groups in average speech activation or inter-subject run-to-run variability in speech activation. Intra-subject run-to-run neural variability was greater in the ASD group and was positively correlated with autism severity in cortical areas associated with speech. Conclusions These findings highlight the importance of understanding intra-subject neural variability in participants with ASD.
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Affiliation(s)
- Elizabeth S. Heller Murray
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Jennifer Segawa
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - F. Isik Karahanoglu
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
| | - Catherine Tocci
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
| | - Jason A. Tourville
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Alfonso Nieto-Castanon
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Helen Tager-Flusberg
- Boston University, Department of Psychological and Brain Sciences, 64 Cummington Mall Boston, MA, 02115
| | - Dara S. Manoach
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
- Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Room 2618, Charlestown, MA 02129
| | - Frank H. Guenther
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
- Boston University, Department of Biomedical Engineering, 44 Cummington Mall Boston, MA, 02115
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Wanazizah H, Susilawati S, Sasmita I. Dental pain behavior of children with autism spectrum disorder at the Biruku Foundation, Bandung City. SCIENTIFIC DENTAL JOURNAL 2022. [DOI: 10.4103/sdj.sdj_34_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Song XK, So WC. The influence of child-based factors and parental inputs on expressive language abilities in children with autism spectrum disorder. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2021; 26:1477-1490. [PMID: 34713741 DOI: 10.1177/13623613211054597] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT Language impairment is one of the early signs of Autism Spectrum Disorder (ASD) that alerts parents to take their children for early diagnosis and intervention. Little is known about how children's autism traits, IQ, initial language abilities and parental inputs influence their language abilities. In addition, only a few studies have compared the relative influence of these factors. The present study addressed these issues by examining the structural language in parent-child spontaneous interactions. Forty-two Cantonese (Chinese)-speaking autistic children aged four to eight were recruited. Their expressive language skills grew rapidly more than 9 months, but their development trajectories varied. Initial expressive language ability is the only significant predictor of child language outcomes and language growth trajectories. In contrast, nonverbal cognition, autism traits, and parents' input do not affect language outcomes in children with ASD. Therefore, early language intervention is crucial for autistic children at all severity and IQ levels.
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Affiliation(s)
- Xue-Ke Song
- The Chinese University of Hong Kong, Hong Kong
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8
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A CNN Deep Local and Global ASD Classification Approach with Continuous Wavelet Transform Using Task-Based FMRI. SENSORS 2021; 21:s21175822. [PMID: 34502710 PMCID: PMC8433893 DOI: 10.3390/s21175822] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/24/2021] [Accepted: 08/25/2021] [Indexed: 11/17/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodegenerative disorder characterized by lingual and social disabilities. The autism diagnostic observation schedule is the current gold standard for ASD diagnosis. Developing objective computer aided technologies for ASD diagnosis with the utilization of brain imaging modalities and machine learning is one of main tracks in current studies to understand autism. Task-based fMRI demonstrates the functional activation in the brain by measuring blood oxygen level-dependent (BOLD) variations in response to certain tasks. It is believed to hold discriminant features for autism. A novel computer aided diagnosis (CAD) framework is proposed to classify 50 ASD and 50 typically developed toddlers with the adoption of CNN deep networks. The CAD system includes both local and global diagnosis in a response to speech task. Spatial dimensionality reduction with region of interest selection and clustering has been utilized. In addition, the proposed framework performs discriminant feature extraction with continuous wavelet transform. Local diagnosis on cingulate gyri, superior temporal gyrus, primary auditory cortex and angular gyrus achieves accuracies ranging between 71% and 80% with a four-fold cross validation technique. The fused global diagnosis achieves an accuracy of 86% with 82% sensitivity, 92% specificity. A brain map indicating ASD severity level for each brain area is created, which contributes to personalized diagnosis and treatment plans.
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Mohammadzaheri F, Koegel LK, Bakhshi E, Khosrowabadi R, Soleymani Z. The Effect of Teaching Initiations on the Communication of Children with Autism Spectrum Disorder: A Randomized Clinical Trial. J Autism Dev Disord 2021; 52:2598-2609. [PMID: 34296374 DOI: 10.1007/s10803-021-05153-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/14/2021] [Indexed: 12/01/2022]
Abstract
This study examined the effect of Pivotal response treatment (PRT) to improve verbal initiations in children with Autism Spectrum Disorder, age 6-12 years old, using a Randomized Clinical Trial design. Intervention was conducted three times a week for 2 months, for a total of 24 one-hour sessions. The PRT intervention taught a variety of questions and attention/assistance-seeking initiations. The treatment as usual (TAU) group received standard language intervention. Results showed that the PRT group made significant improvements in their number of verbal initiations as well as collateral gains in general communicative skills and mean length of utterance (MLU) compared to the TAU group. Theoretical implications of including motivational approaches to develop social initiations are reviewed.
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Affiliation(s)
- Fereshteh Mohammadzaheri
- Department of Speech Therapy, School of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran
| | - Lynn Kern Koegel
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Enayatollah Bakhshi
- Department of Biostatistics and Epidemiology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University GC, Tehran, Iran
| | - Zahra Soleymani
- Department of Speech Therapy, School of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran.
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10
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Sex Differences in Functional Connectivity Between Resting State Brain Networks in Autism Spectrum Disorder. J Autism Dev Disord 2021; 52:3088-3101. [PMID: 34272649 PMCID: PMC9213274 DOI: 10.1007/s10803-021-05191-6] [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] [Accepted: 07/06/2021] [Indexed: 11/05/2022]
Abstract
Functional brain connectivity (FBC) has previously been examined in autism spectrum disorder (ASD) between-resting-state networks (RSNs) using a highly sensitive and reproducible hypothesis-free approach. However, results have been inconsistent and sex differences have only recently been taken into consideration using this approach. We estimated main effects of diagnosis and sex and a diagnosis by sex interaction on between-RSNs FBC in 83 ASD (40 females/43 males) and 85 typically developing controls (TC; 43 females/42 males). We found increased connectivity between the default mode (DM) and (a) the executive control networks in ASD (vs. TC); (b) the cerebellum networks in males (vs. females); and (c) female-specific altered connectivity involving visual, language and basal ganglia (BG) networks in ASD—in suggestive compatibility with ASD cognitive and neuroscientific theories.
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Alho J, Bharadwaj H, Khan S, Mamashli F, Perrachione TK, Losh A, McGuiggan NM, Joseph RM, Hämäläinen MS, Kenet T. Altered maturation and atypical cortical processing of spoken sentences in autism spectrum disorder. Prog Neurobiol 2021; 203:102077. [PMID: 34033856 DOI: 10.1016/j.pneurobio.2021.102077] [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: 01/15/2021] [Revised: 04/14/2021] [Accepted: 05/19/2021] [Indexed: 10/21/2022]
Abstract
Autism spectrum disorder (ASD) is associated with widespread receptive language impairments, yet the neural mechanisms underlying these deficits are poorly understood. Neuroimaging has shown that processing of socially-relevant sounds, including speech and non-speech, is atypical in ASD. However, it is unclear how the presence of lexical-semantic meaning affects speech processing in ASD. Here, we recorded magnetoencephalography data from individuals with ASD (N = 22, ages 7-17, 4 females) and typically developing (TD) peers (N = 30, ages 7-17, 5 females) during unattended listening to meaningful auditory speech sentences and meaningless jabberwocky sentences. After adjusting for age, ASD individuals showed stronger responses to meaningless jabberwocky sentences than to meaningful speech sentences in the same left temporal and parietal language regions where TD individuals exhibited stronger responses to meaningful speech. Maturational trajectories of meaningful speech responses were atypical in temporal, but not parietal, regions in ASD. Temporal responses were associated with ASD severity, while parietal responses were associated with aberrant involuntary attentional shifting in ASD. Our findings suggest a receptive speech processing dysfunction in ASD, wherein unattended meaningful speech elicits abnormal engagement of the language system, while unattended meaningless speech, filtered out in TD individuals, engages the language system through involuntary attention capture.
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Affiliation(s)
- Jussi Alho
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Hari Bharadwaj
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Speech, Language, and Hearing Sciences, and Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Sheraz Khan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Fahimeh Mamashli
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tyler K Perrachione
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, USA
| | - Ainsley Losh
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Graduate School of Education, University of California, Riverside, CA, USA
| | - Nicole M McGuiggan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Matti S Hämäläinen
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tal Kenet
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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12
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Haweel R, Shalaby A, Mahmoud A, Seada N, Ghoniemy S, Ghazal M, Casanova MF, Barnes GN, El-Baz A. A robust DWT-CNN-based CAD system for early diagnosis of autism using task-based fMRI. Med Phys 2021; 48:2315-2326. [PMID: 33378589 DOI: 10.1002/mp.14692] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 11/27/2020] [Accepted: 12/17/2020] [Indexed: 02/06/2023] Open
Abstract
PURPOSE Task-based fMRI (TfMRI) is a diagnostic imaging modality for observing the effects of a disease or other condition on the functional activity of the brain. Autism spectrum disorder (ASD) is a pervasive developmental disorder associated with impairments in social and linguistic abilities. Machine learning algorithms have been widely utilized for brain imaging aiming for objective ASD diagnostics. Recently, deep learning methods have been gaining more attention for fMRI classification. The goal of this paper is to develop a convolutional neural network (CNN)-based framework to help in global diagnosis of ASD using TfMRI data that are collected from a response to speech experiment. METHODS To achieve this goal, the proposed framework adopts a novel imaging marker integrating both spatial and temporal information that are related to the functional activity of the brain. The developed pipeline consists of three main components. In the first step, the collected TfMRI data are preprocessed and parcellated using the Harvard-Oxford probabilistic atlas included with the fMRIB Software Library (FSL). Second, a group analysis using FSL is performed between ASD and typically developing (TD) children to identify significantly activated brain areas in response to the speech task. In order to reduce brain spatial dimensionality, a K-means clustering technique is performed on such significant brain areas. Informative blood oxygen level-dependent (BOLD) signals are extracted from each cluster. A compression step for each extracted BOLD signal using discrete wavelet transform (DWT) has been proposed. The adopted wavelets are similar to the expected hemodynamic response which enables DWT to compress the BOLD signal while highlighting its activation information. Finally, a deep learning 2D CNN network is used to classify the patients as ASD or TD based on extracted features from the previous step. RESULTS Preliminary results on 100 TfMRI dataset (50 ASD, 50 TD) obtain 80% correct global classification using tenfold cross validation (with sensitivity = 84%, specificity = 76%). CONCLUSION The experimental results show the high accuracy of the proposed framework and hold promise for the presented framework as a helpful adjunct to currently used ASD diagnostic tools.
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Affiliation(s)
- Reem Haweel
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, KY, 40208, USA
- Computer Systems Department, Faculty of Computer and Information Sciences, University of Ain Shams, Cairo, 11566, Egypt
| | - Ahmed Shalaby
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, KY, 40208, USA
| | - Ali Mahmoud
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, KY, 40208, USA
| | - Noha Seada
- Computer Systems Department, Faculty of Computer and Information Sciences, University of Ain Shams, Cairo, 11566, Egypt
| | - Said Ghoniemy
- Computer Systems Department, Faculty of Computer and Information Sciences, University of Ain Shams, Cairo, 11566, Egypt
| | - Mohammed Ghazal
- Department of Electrical and Computer Engineering, Abu Dhabi University, Abu Dhabi, 59911, UAE
| | - Manuel F Casanova
- Biomedical Sciences, University of South Carolina, Greenville, SC, 29607, USA
| | - Gregory N Barnes
- Department of Neurology, University of Louisville, Louisville, KY, 40208, USA
| | - Ayman El-Baz
- Department of Bioengineering, University of Louisville, KY, 40208, USA
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You Y, Correas A, Jao Keehn RJ, Wagner LC, Rosen BQ, Beaton LE, Gao Y, Brocklehurst WT, Fishman I, Müller RA, Marinkovic K. MEG Theta during Lexico-Semantic and Executive Processing Is Altered in High-Functioning Adolescents with Autism. Cereb Cortex 2021; 31:1116-1130. [PMID: 33073290 DOI: 10.1093/cercor/bhaa279] [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: 02/26/2020] [Revised: 08/28/2020] [Accepted: 08/30/2020] [Indexed: 02/06/2023] Open
Abstract
Neuroimaging studies have revealed atypical activation during language and executive tasks in individuals with autism spectrum disorders (ASD). However, the spatiotemporal stages of processing associated with these dysfunctions remain poorly understood. Using an anatomically constrained magnetoencephalography approach, we examined event-related theta oscillations during a double-duty lexical decision task that combined demands on lexico-semantic processing and executive functions. Relative to typically developing peers, high-functioning adolescents with ASD had lower performance accuracy on trials engaging selective semantic retrieval and cognitive control. They showed an early overall theta increase in the left fusiform cortex followed by greater activity in the left-lateralized temporal (starting at ~250 ms) and frontal cortical areas (after ~450 ms) known to contribute to language processing. During response preparation and execution, the ASD group exhibited elevated theta in the anterior cingulate cortex, indicative of greater engagement of cognitive control. Simultaneously increased activity in the ipsilateral motor cortex may reflect a less lateralized and suboptimally organized motor circuitry. Spanning early sensory-specific and late response selection stages, the higher event-related theta responsivity in ASD may indicate compensatory recruitment to offset inefficient lexico-semantic retrieval under cognitively demanding conditions. Together, these findings provide further support for atypical language and executive functions in high-functioning ASD.
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Affiliation(s)
- Yuqi You
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Angeles Correas
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - R Joanne Jao Keehn
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Laura C Wagner
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Burke Q Rosen
- Department of Neurosciences, University of California San Diego, San Diego, CA 92093, USA
| | - Lauren E Beaton
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Yangfeifei Gao
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California San Diego, San Diego, CA 92120, USA
| | | | - Inna Fishman
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California San Diego, San Diego, CA 92120, USA
| | - Ralph-Axel Müller
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California San Diego, San Diego, CA 92120, USA
| | - Ksenija Marinkovic
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California San Diego, San Diego, CA 92120, USA.,Department of Radiology, University of California San Diego, San Diego, CA 92093, USA
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14
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Vogindroukas I, Chelas EN, Petridis NE. Developmental Profile of Social Communication: Findings in Typical Developing Greek Children. Folia Phoniatr Logop 2020; 73:195-204. [PMID: 33326972 DOI: 10.1159/000511901] [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: 12/24/2019] [Accepted: 09/24/2020] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES The Developmental Profile of Social Communication (DPSC) is based on the communication and language development in children with social communication difficulties. DPSC facilitates understanding of the challenges these children face in social interaction, communication, and linguistic development. It utilizes clinician and parent responses to build the developmental profiles of individuals. The profile allows clinicians to determine the therapeutic goals for improved cooperation and communication in various contexts. In addition, it provides insight into the parents' perspective. The aim of this study is to present the preliminary results of the DPSC in typically developing Greek children. METHODS The DPSC, a 112-item questionnaire, was administered to 357 parents of typically developing children aged 2-7.5 years using a 3-scale rating of answers. It was applied electronically via Google forms, and parents were able to ask for clarification on questions. All answers were categorized and then analyzed under independent variables. RESULTS Descriptive and hypothesis testing were used to summarize participant characteristics and performance. Findings suggest that children >7.5 years tended to develop most of the rated skills of DPSC adequately. CONCLUSIONS It was determined that the DPSC questionnaire is an easily administered tool that enables the evaluation of the social communication abilities of children of different ages.
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Affiliation(s)
| | | | - Nikolaos E Petridis
- Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
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15
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Abstract
Individuals with autism spectrum disorder (ASD) reportedly possess preserved or superior music-processing skills compared to their typically developing counterparts. We examined auditory imagery and earworms (tunes that get "stuck" in the head) in adults with ASD and controls. Both groups completed a short earworm questionnaire together with the Bucknell Auditory Imagery Scale. Results showed poorer auditory imagery in the ASD group for all types of auditory imagery. However, the ASD group did not report fewer earworms than matched controls. These data suggest a possible basis in poor auditory imagery for poor prosody in ASD, but also highlight a separability between auditory imagery and control of musical memories. The separability is present in the ASD group but not in typically developing individuals.
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Affiliation(s)
- Alex Bacon
- School of Psychology and Clinical Language Sciences, University of Reading, Earley Gate, Whiteknights, Reading, RG6 6AL, UK
| | - C Philip Beaman
- School of Psychology and Clinical Language Sciences, University of Reading, Earley Gate, Whiteknights, Reading, RG6 6AL, UK.
| | - Fang Liu
- School of Psychology and Clinical Language Sciences, University of Reading, Earley Gate, Whiteknights, Reading, RG6 6AL, UK
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16
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Zhao X, Rangaprakash D, Yuan B, Denney TS, Katz JS, Dretsch MN, Deshpande G. Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning. FRONTIERS IN APPLIED MATHEMATICS AND STATISTICS 2018; 4:25. [PMID: 30393630 PMCID: PMC6214192 DOI: 10.3389/fams.2018.00025] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Many brain-based disorders are traditionally diagnosed based on clinical interviews and behavioral assessments, which are recognized to be largely imperfect. Therefore, it is necessary to establish neuroimaging-based biomarkers to improve diagnostic precision. Resting-state functional magnetic resonance imaging (rs-fMRI) is a promising technique for the characterization and classification of varying disorders. However, most of these classification methods are supervised, i.e., they require a priori clinical labels to guide classification. In this study, we adopted various unsupervised clustering methods using static and dynamic rs-fMRI connectivity measures to investigate whether the clinical diagnostic grouping of different disorders is grounded in underlying neurobiological and phenotypic clusters. In order to do so, we derived a general analysis pipeline for identifying different brain-based disorders using genetic algorithm-based feature selection, and unsupervised clustering methods on four different datasets; three of them-ADNI, ADHD-200, and ABIDE-which are publicly available, and a fourth one-PTSD and PCS-which was acquired in-house. Using these datasets, the effectiveness of the proposed pipeline was verified on different disorders: Attention Deficit Hyperactivity Disorder (ADHD), Alzheimer's Disease (AD), Autism Spectrum Disorder (ASD), Post-Traumatic Stress Disorder (PTSD), and Post-Concussion Syndrome (PCS). For ADHD and AD, highest similarity was achieved between connectivity and phenotypic clusters, whereas for ASD and PTSD/PCS, highest similarity was achieved between connectivity and clinical diagnostic clusters. For multi-site data (ABIDE and ADHD-200), we report site-specific results. We also reported the effect of elimination of outlier subjects for all four datasets. Overall, our results suggest that neurobiological and phenotypic biomarkers could potentially be used as an aid by the clinician, in additional to currently available clinical diagnostic standards, to improve diagnostic precision. Data and source code used in this work is publicly available at https://github.com/xinyuzhao/identification-of-brain-based-disorders.git.
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Affiliation(s)
- Xinyu Zhao
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Quora, Inc., Mountain View, CA, United States
| | - D. Rangaprakash
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Bowen Yuan
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
| | - Thomas S. Denney
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychology, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Auburn University, University of Alabama at Birmingham, Birmingham, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
| | - Jeffrey S. Katz
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychology, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Auburn University, University of Alabama at Birmingham, Birmingham, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
| | - Michael N. Dretsch
- Human Dimension Division, HQ TRADOC, Fort Eustis, VA, United States
- U.S. Army Aeromedical Research Laboratory, Fort Rucker, AL, United States
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychology, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Auburn University, University of Alabama at Birmingham, Birmingham, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
- Center for Health Ecology and Equity Research, Auburn University, Auburn, AL, United States
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17
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Tryfon A, Foster NEV, Sharda M, Hyde KL. Speech perception in autism spectrum disorder: An activation likelihood estimation meta-analysis. Behav Brain Res 2017; 338:118-127. [PMID: 29074403 DOI: 10.1016/j.bbr.2017.10.025] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Revised: 10/13/2017] [Accepted: 10/20/2017] [Indexed: 02/06/2023]
Abstract
Autism spectrum disorder (ASD) is often characterized by atypical language profiles and auditory and speech processing. These can contribute to aberrant language and social communication skills in ASD. The study of the neural basis of speech perception in ASD can serve as a potential neurobiological marker of ASD early on, but mixed results across studies renders it difficult to find a reliable neural characterization of speech processing in ASD. To this aim, the present study examined the functional neural basis of speech perception in ASD versus typical development (TD) using an activation likelihood estimation (ALE) meta-analysis of 18 qualifying studies. The present study included separate analyses for TD and ASD, which allowed us to examine patterns of within-group brain activation as well as both common and distinct patterns of brain activation across the ASD and TD groups. Overall, ASD and TD showed mostly common brain activation of speech processing in bilateral superior temporal gyrus (STG) and left inferior frontal gyrus (IFG). However, the results revealed trends for some distinct activation in the TD group showing additional activation in higher-order brain areas including left superior frontal gyrus (SFG), left medial frontal gyrus (MFG), and right IFG. These results provide a more reliable neural characterization of speech processing in ASD relative to previous single neuroimaging studies and motivate future work to investigate how these brain signatures relate to behavioral measures of speech processing in ASD.
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Affiliation(s)
- Ana Tryfon
- International Laboratory for Brain, Music, and Sound Research (BRAMS), Pavillon 1420 Mont-Royal, Department of Psychology, University of Montreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec, H3C 3J7, Canada; Faculty of Medicine, McIntyre Medical Building, McGill University, 3655 Sir William Osler, Montreal, Quebec H3G 1Y6, Canada.
| | - Nicholas E V Foster
- International Laboratory for Brain, Music, and Sound Research (BRAMS), Pavillon 1420 Mont-Royal, Department of Psychology, University of Montreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec, H3C 3J7, Canada
| | - Megha Sharda
- International Laboratory for Brain, Music, and Sound Research (BRAMS), Pavillon 1420 Mont-Royal, Department of Psychology, University of Montreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec, H3C 3J7, Canada
| | - Krista L Hyde
- International Laboratory for Brain, Music, and Sound Research (BRAMS), Pavillon 1420 Mont-Royal, Department of Psychology, University of Montreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec, H3C 3J7, Canada; Faculty of Medicine, McIntyre Medical Building, McGill University, 3655 Sir William Osler, Montreal, Quebec H3G 1Y6, Canada
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18
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Mulhern T, Lydon S, Healy O, Mollaghan G, Ramey D, Leoni M. A systematic review and evaluation of procedures for the induction of speech among persons with developmental disabilities. Dev Neurorehabil 2017; 20:207-227. [PMID: 27058303 DOI: 10.3109/17518423.2016.1150360] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Deficits in vocal speech are common among those with developmental disabilities. This review examines interventions for teaching speech to individuals who presented as nonspeaking, or with low levels of vocalizations at baseline, and assesses evidence-based practice in this area. METHODS Systematic searches identified 78 studies suitable for inclusion. These studies were evaluated in terms of (a) participants, (b) intervention, (c) intervention setting, (d) intervention agent, (e) treatment efficacy, (f) generalization and maintenance of treatment effects, and (g) research rigor. RESULTS A variety of interventions, primarily behavioral, intended to induce vocal speech were delivered to participants with developmental disabilities aged between six months and 57 years. Treatment efficacy was variable (PND M = 52.9%; range 0%-100%); however, results indicated that behavioral interventions constituted evidence-based practice. Non-behavioral strategies were shown to have received insufficient research evaluation to date. CONCLUSION Results indicate that a number of procedures can induce speech among individuals with developmental disabilities.
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Affiliation(s)
- Teresa Mulhern
- a School of Psychology , National University of Ireland , Galway , Ireland
| | - Sinéad Lydon
- a School of Psychology , National University of Ireland , Galway , Ireland.,b School of Psychology , Trinity College Dublin , Dublin 2 , Ireland
| | - Olive Healy
- b School of Psychology , Trinity College Dublin , Dublin 2 , Ireland
| | - Gerard Mollaghan
- a School of Psychology , National University of Ireland , Galway , Ireland
| | - Devon Ramey
- b School of Psychology , Trinity College Dublin , Dublin 2 , Ireland
| | - Mauro Leoni
- c Disability Department , Fondazione Sospiro Onlus , CR , Italy
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19
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Mamashli F, Khan S, Bharadwaj H, Michmizos K, Ganesan S, Garel KLA, Ali Hashmi J, Herbert MR, Hämäläinen M, Kenet T. Auditory processing in noise is associated with complex patterns of disrupted functional connectivity in autism spectrum disorder. Autism Res 2016; 10:631-647. [PMID: 27910247 DOI: 10.1002/aur.1714] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Revised: 09/09/2016] [Accepted: 09/16/2016] [Indexed: 11/12/2022]
Abstract
Autism spectrum disorder (ASD) is associated with difficulty in processing speech in a noisy background, but the neural mechanisms that underlie this deficit have not been mapped. To address this question, we used magnetoencephalography to compare the cortical responses between ASD and typically developing (TD) individuals to a passive mismatch paradigm. We repeated the paradigm twice, once in a quiet background, and once in the presence of background noise. We focused on both the evoked mismatch field (MMF) response in temporal and frontal cortical locations, and functional connectivity with spectral specificity between those locations. In the quiet condition, we found common neural sources of the MMF response in both groups, in the right temporal gyrus and inferior frontal gyrus (IFG). In the noise condition, the MMF response in the right IFG was preserved in the TD group, but reduced relative to the quiet condition in ASD group. The MMF response in the right IFG also correlated with severity of ASD. Moreover, in noise, we found significantly reduced normalized coherence (deviant normalized by standard) in ASD relative to TD, in the beta band (14-25 Hz), between left temporal and left inferior frontal sub-regions. However, unnormalized coherence (coherence during deviant or standard) was significantly increased in ASD relative to TD, in multiple frequency bands. Our findings suggest increased recruitment of neural resources in ASD irrespective of the task difficulty, alongside a reduction in top-down modulations, usually mediated by the beta band, needed to mitigate the impact of noise on auditory processing. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 631-647. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
- Fahimeh Mamashli
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Sheraz Khan
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,McGovern Institute for Brain Research Massachusetts Institute of Technology, Boston, Massachusetts
| | - Hari Bharadwaj
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Konstantinos Michmizos
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,McGovern Institute for Brain Research Massachusetts Institute of Technology, Boston, Massachusetts
| | - Santosh Ganesan
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Keri-Lee A Garel
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Javeria Ali Hashmi
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Martha R Herbert
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.,Department of Neuroscience and Biomedical Engineering, Aalto University School of Science Espoo, Finland
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Tal Kenet
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
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20
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Sperdin HF, Schaer M. Aberrant Development of Speech Processing in Young Children with Autism: New Insights from Neuroimaging Biomarkers. Front Neurosci 2016; 10:393. [PMID: 27610073 PMCID: PMC4997090 DOI: 10.3389/fnins.2016.00393] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 08/10/2016] [Indexed: 12/13/2022] Open
Abstract
From the time of birth, a newborn is continuously exposed and naturally attracted to human voices, and as he grows, he becomes increasingly responsive to these speech stimuli, which are strong drivers for his language development and knowledge acquisition about the world. In contrast, young children with autism spectrum disorder (ASD) are often insensitive to human voices, failing to orient and respond to them. Failure to attend to speech in turn results in altered development of language and social-communication skills. Here, we review the critical role of orienting to speech in ASD, as well as the neural substrates of human voice processing. Recent functional neuroimaging and electroencephalography studies demonstrate that aberrant voice processing could be a promising marker to identify ASD very early on. With the advent of refined brain imaging methods, coupled with the possibility of screening infants and toddlers, predictive brain function biomarkers are actively being examined and are starting to emerge. Their timely identification might not only help to differentiate between phenotypes, but also guide the clinicians in setting up appropriate therapies, and better predicting or quantifying long-term outcome.
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Affiliation(s)
- Holger F. Sperdin
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva School of MedicineGeneva, Switzerland
| | - Marie Schaer
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva School of MedicineGeneva, Switzerland
- Stanford Cognitive & Systems Neuroscience Laboratory, Stanford University School of MedicinePalo Alto, CA, USA
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Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has a strong genetic basis, and is heterogeneous in its etiopathogenesis and clinical presentation. Neuroimaging studies, in concert with neuropathological and clinical research, have been instrumental in delineating trajectories of development in children with ASD. Structural neuroimaging has revealed ASD to be a disorder with general and regional brain enlargement, especially in the frontotemporal cortices, while functional neuroimaging studies have highlighted diminished connectivity, especially between frontal-posterior regions. The diverse and specific neuroimaging findings may represent potential neuroendophenotypes, and may offer opportunities to further understand the etiopathogenesis of ASD, predict treatment response, and lead to the development of new therapies.
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Affiliation(s)
- Rajneesh Mahajan
- Center for Neurodevelopmental and Imaging Research (CNIR), Kennedy Krieger Institute, Baltimore, Maryland
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, Maryland
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Stewart H. Mostofsky
- Center for Neurodevelopmental and Imaging Research (CNIR), Kennedy Krieger Institute, Baltimore, Maryland
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, Maryland
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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22
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Peeva MG, Tourville JA, Agam Y, Holland B, Manoach DS, Guenther FH. White matter impairment in the speech network of individuals with autism spectrum disorder. NEUROIMAGE-CLINICAL 2013; 3:234-41. [PMID: 24273708 PMCID: PMC3815014 DOI: 10.1016/j.nicl.2013.08.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2013] [Revised: 08/06/2013] [Accepted: 08/21/2013] [Indexed: 11/04/2022]
Abstract
Impairments in language and communication are core features of Autism Spectrum Disorder (ASD), and a substantial percentage of children with ASD do not develop speech. ASD is often characterized as a disorder of brain connectivity, and a number of studies have identified white matter impairments in affected individuals. The current study investigated white matter integrity in the speech network of high-functioning adults with ASD. Diffusion tensor imaging (DTI) scans were collected from 18 participants with ASD and 18 neurotypical participants. Probabilistic tractography was used to estimate the connection strength between ventral premotor cortex (vPMC), a cortical region responsible for speech motor planning, and five other cortical regions in the network of areas involved in speech production. We found a weaker connection between the left vPMC and the supplementary motor area in the ASD group. This pathway has been hypothesized to underlie the initiation of speech motor programs. Our results indicate that a key pathway in the speech production network is impaired in ASD, and that this impairment can occur even in the presence of normal language abilities. Therapies that result in normalization of this pathway may hold particular promise for improving speech output in ASD. We used diffusion tensor imaging to measure white matter (WM) tracts in autism. Autistic participants were high-functioning individuals with normal language skills. WM between left supplementary motor and premotor areas is impaired in autism. This tract is believed to be involved in the initiation of speech articulation. Speech production may be impaired in the absence of language deficits in autism.
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Affiliation(s)
- M G Peeva
- Center for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, USA
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