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Zapparrata NM, Brooks PJ, Ober TM. Slower Processing Speed in Autism Spectrum Disorder: A Meta-analytic Investigation of Time-Based Tasks. J Autism Dev Disord 2023; 53:4618-4640. [PMID: 36112302 DOI: 10.1007/s10803-022-05736-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2022] [Indexed: 11/28/2022]
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition affecting information processing across domains. The current meta-analysis investigated whether slower processing speed is associated with the ASD neurocognitive profile and whether findings hold across different time-based tasks and stimuli (social vs. nonsocial; linguistic vs. nonlinguistic). Mean RTs of ASD and age-matched neurotypical comparison groups (N = 893 ASD, 1063 neurotypical; mean age ASD group = 17 years) were compared across simple RT, choice RT, and interference control tasks (44 studies, 106 effects) using robust variance estimation meta-analysis. Simple RT tasks required participants to respond to individual stimuli, whereas choice RT tasks required forced-choice responses to two or more stimuli. Interference control tasks required a decision in the context of a distractor or priming stimulus; in an effort to minimize inhibitory demands, we extracted RTs only from baseline and congruent conditions of such tasks. All tasks required nonverbal (motor) responses. The overall effect-size estimate indicated significantly longer mean RTs in ASD groups (g = .35, 95% CI = .16; .54) than comparison groups. Task type moderated effects, with larger estimates drawn from simple RT tasks than interference control tasks. However, across all three task types, ASD groups exhibited significantly longer mean RTs than comparison groups. Stimulus type and age did not moderate effects. Generalized slowing may be a domain-general characteristic of ASD with potential consequences for social, language, and motor development. Assessing processing speed may inform development of interventions to support autistic individuals and their diverse cognitive profiles.
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Affiliation(s)
- Nicole M Zapparrata
- The College of Staten Island, City University of New York, 2800 Victory Blvd, Staten Island, NY, 10314, USA.
- Educational Psychology Program, The CUNY Graduate Center, 365 Fifth Ave., New York, NY, 10016, USA.
| | - Patricia J Brooks
- The College of Staten Island, City University of New York, 2800 Victory Blvd, Staten Island, NY, 10314, USA
- Educational Psychology Program, The CUNY Graduate Center, 365 Fifth Ave., New York, NY, 10016, USA
| | - Teresa M Ober
- University of Notre Dame, Notre Dame, IN, 46556, USA
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Huang X, Ming Y, Zhao W, Feng R, Zhou Y, Wu L, Wang J, Xiao J, Li L, Shan X, Cao J, Kang X, Chen H, Duan X. Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain. Mol Autism 2023; 14:41. [PMID: 37899464 PMCID: PMC10614412 DOI: 10.1186/s13229-023-00573-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 10/22/2023] [Indexed: 10/31/2023] Open
Abstract
OBJECTIVE There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have been divergent. The development of autistic people in early childhood is clouded by the concurrently rapid brain growth, which might lead to the inconsistent findings of atypical WM microstructure in autism. Here, we aimed to reveal the developmental nature of autistic children and delineate atypical WM microstructure throughout early childhood while taking developmental considerations into account. METHOD In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 autistic children and 100 typically developing children (TDC), aged 4-7 years. Developmental prediction modeling using support vector regression based on TDC participants was conducted to estimate the WM atypical development index of autistic children. Then, subgroups of autistic children were identified by using the k-means clustering method and were compared to each other on the basis of demographic information, WM atypical development index, and autistic trait by using two-sample t-test. Relationship of the WM atypical development index with age was estimated by using partial correlation. Furthermore, we performed threshold-free cluster enhancement-based two-sample t-test for the group comparison in WM microstructures of each subgroup of autistic children with the rematched subsets of TDC. RESULTS We clustered autistic children into two subgroups according to WM atypical development index. The two subgroups exhibited distinct developmental stages and age-dependent diversity. WM atypical development index was found negatively associated with age. Moreover, an inverse pattern of atypical WM microstructures and different clinical manifestations in the two stages, with subgroup 1 showing overgrowth with low level of autistic traits and subgroup 2 exhibiting delayed maturation with high level of autistic traits, were revealed. CONCLUSION This study illustrated age-dependent heterogeneity in early childhood autistic children and delineated developmental stage-specific difference that ranged from an overgrowth pattern to a delayed pattern. Trial registration This study has been registered at ClinicalTrials.gov (Identifier: NCT02807766) on June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ).
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Affiliation(s)
- Xinyue Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Yating Ming
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Weixing Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Rui Feng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Yuanyue Zhou
- Department of Medical Psychology, The First Affiliated Hospital, Hainan Medical University, Haikou, 571199, Hainan, People's Republic of China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, 150086, People's Republic of China
| | - Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, 150086, People's Republic of China
| | - Jinming Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Lei Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Xiaolong Shan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Jing Cao
- Child Rehabilitation Unit, Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan Bayi Rehabilitation Center, Chengdu, 611135, People's Republic of China
| | - Xiaodong Kang
- Child Rehabilitation Unit, Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan Bayi Rehabilitation Center, Chengdu, 611135, People's Republic of China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
- MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
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Zapparrata NM, Brooks PJ, Ober T. Developmental Language Disorder Is Associated With Slower Processing Across Domains: A Meta-Analysis of Time-Based Tasks. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2023; 66:325-346. [PMID: 36603228 DOI: 10.1044/2022_jslhr-22-00221] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
PURPOSE Individuals with developmental language disorder (DLD) often exhibit slower processing on time-based tasks in comparison with age-matched peers. Processing speed has been linked to various linguistic skills and might serve as a global indicator of individual differences in language abilities. Despite an extensive literature on processing speed in DLD, it remains unclear whether slower processing is domain general or restricted to linguistic and/or auditory tasks. METHOD This meta-analysis used robust variance estimation to compare response/reaction times (RTs) of DLD and age-matched groups (N = 812 DLD, 870 neurotypical; M age [DLD] = 8.9 years, range: 4.3-22.7 years). Moderators included task (simple RT, choice RT, naming, congruent/baseline conditions of interference control tasks), stimulus type (linguistic/nonlinguistic), stimulus modality (auditory/nonauditory), and response modality (verbal/nonverbal). Age and publication year were covariates. RESULTS The overall effect based on 46 studies and 144 estimates indicated longer mean RTs in DLD groups (g = .47, p < .001, 95% CI [.38, .55]). Moderator analyses indicated larger effects when tasks required verbal as opposed to nonverbal responses. No other moderators approached significance. All subgroup analyses were significant, indicating longer mean RTs in DLD groups across tasks, stimulus types, stimulus modalities, and response modalities. CONCLUSIONS Individuals with DLD exhibit longer RTs across verbal and nonverbal tasks, which may contribute to observed difficulties in language, motor skills, and executive functioning. Simple processing speed measures should be included in screening for language delays but may not be suitable for differential diagnosis, given that slower processing may occur across multiple disorders. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.21809355.
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Affiliation(s)
| | - Patricia J Brooks
- Program in Educational Psychology, CUNY Graduate Center, New York, NY
- Department of Psychology, College of Staten Island, NY
| | - Teresa Ober
- Department of Psychology, University of Notre Dame, IN
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Zhang M, Hu X, Jiao J, Yuan D, Li S, Luo T, Wang M, Situ M, Sun X, Huang Y. Brain white matter microstructure abnormalities in children with optimal outcome from autism: a four-year follow-up study. Sci Rep 2022; 12:20151. [PMID: 36418886 PMCID: PMC9684497 DOI: 10.1038/s41598-022-21085-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/22/2022] [Indexed: 11/24/2022] Open
Abstract
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder, with only a small proportion of people obtaining optimal outcomes. We do not know if children with ASD exhibit abnormalities in the white matter (WM) microstructure or if this pattern would predict ASD prognosis in a longitudinal study. 182 children with ASD were recruited for MRI and clinical assessment; 111 completed a four-year follow-up visit (30 with optimal outcomes, ASD-; 81 with persistent diagnosis, ASD+). Additionally, 72 typically developing controls (TDC) were recruited. The microstructural integrity of WM fiber tracts was revealed using tract-based spatial statistics (TBSS) and probabilistic tractography analyses. We examined the neuroimaging abnormality associated with ASD and its relationship to ASD with optimal outcome. The ASD+ and TDC groups were propensity score matched to the ASD- group in terms of age, gender, and IQ. TBSS indicated that children with ASD exhibited abnormalities in the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and extending to the anterior thalamic radiation (ATR) and cingulum; whereas the ASD+ group showed more severe abnormalities than the ASD- group. Probabilistic tractography analysis revealed that ASD+ group exhibited lower Fractional Anisotropy (FA) of the left superior thalamic radiation (STR L) than ASD- group, and that FA value of the STR L was a significant predictor of optimal outcome (EX(B), 6.25; 95% CI 2.50-15.63; p < 0.001). Children with ASD showed significant variations in SLF_L and STR_L, and STR_L was a predictor of 'ASD with optimal outcome'. Our findings may aid in comprehension of the mechanisms of 'ASD with optimal outcome'.
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Affiliation(s)
- Manxue Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
- The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiao Hu
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
- West China Second Hospital of Sichuan University, Chengdu, China
| | - Jian Jiao
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Danfeng Yuan
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Sixun Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Tingting Luo
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Meiwen Wang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Mingjing Situ
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xueli Sun
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
| | - Yi Huang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
- Brain Research Center, West China Hospital of Sichuan University, Chengdu, China.
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Prigge MBD, Bigler ED, Lange N, Morgan J, Froehlich A, Freeman A, Kellett K, Kane KL, King CK, Taylor J, Dean DC, King JB, Anderson JS, Zielinski BA, Alexander AL, Lainhart JE. Longitudinal Stability of Intellectual Functioning in Autism Spectrum Disorder: From Age 3 Through Mid-adulthood. J Autism Dev Disord 2022; 52:4490-4504. [PMID: 34677753 PMCID: PMC9090201 DOI: 10.1007/s10803-021-05227-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/29/2021] [Indexed: 12/02/2022]
Abstract
Intelligence (IQ) scores are used in educational and vocational planning for individuals with autism spectrum disorder (ASD) yet little is known about the stability of IQ throughout development. We examined longitudinal age-related IQ stability in 119 individuals with ASD (3-36 years of age at first visit) and 128 typically developing controls. Intelligence measures were collected over a 20-year period. In ASD, Full Scale (FSIQ) and Verbal (VIQ) Intelligence started lower in childhood and increased at a greater rate with age relative to the control group. By early adulthood, VIQ and working memory stabilized, whereas nonverbal and perceptual scores continued to change. Our results suggest that in individuals with ASD, IQ estimates may be dynamic in childhood and young adulthood.
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Affiliation(s)
- Molly B D Prigge
- Department of Radiology and Imaging Sciences, Radiology Research, University of Utah, 729 Arapeen Drive, Salt Lake City, UT, 84108, USA.
| | - Erin D Bigler
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Department of Neurology, University of California-Davis, Davis, CA, USA
| | - Nicholas Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, MA, USA
| | - Jubel Morgan
- Department of Radiology and Imaging Sciences, Radiology Research, University of Utah, 729 Arapeen Drive, Salt Lake City, UT, 84108, USA
| | - Alyson Froehlich
- Department of Psychology, University of Utah, Salt Lake City, UT, USA
| | - Abigail Freeman
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristina Kellett
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Karen L Kane
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Carolyn K King
- Department of Radiology and Imaging Sciences, Radiology Research, University of Utah, 729 Arapeen Drive, Salt Lake City, UT, 84108, USA
| | - June Taylor
- Department of Radiology and Imaging Sciences, Radiology Research, University of Utah, 729 Arapeen Drive, Salt Lake City, UT, 84108, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Jace B King
- Department of Radiology and Imaging Sciences, Radiology Research, University of Utah, 729 Arapeen Drive, Salt Lake City, UT, 84108, USA
| | - Jeff S Anderson
- Department of Radiology and Imaging Sciences, Radiology Research, University of Utah, 729 Arapeen Drive, Salt Lake City, UT, 84108, USA
| | - Brandon A Zielinski
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Janet E Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
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Cai Y, Zhao J, Wang L, Xie Y, Fan X. Altered topological properties of white matter structural network in adults with autism spectrum disorder. Asian J Psychiatr 2022; 75:103211. [PMID: 35907341 DOI: 10.1016/j.ajp.2022.103211] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a complex developmental disability and is currently viewed as a disorder of brain connectivity in which white matter abnormalities. However, the majority of the research to date has focused on children with ASD. Understanding the topological organization of the white matter structural network in adults may help uncover the nature of ASD pathology in adulthood. METHOD This study investigated the topological properties of white matter structural network using diffusion tensor imaging and graph theory analysis in a sample of 32 adults with ASD compared to 35 matched typically developing (TD) controls. Group differences in global and nodal topological metrics were compared. The relationships between the altered network metrics and the severity of clinical symptoms were calculated. RESULTS Compared to TD controls, ASD patients exhibited decreased small-worldness and increased global efficiency. In addition, the reduced nodal efficiency and increased nodal degree were found in the frontal (e.g., the inferior frontal gyrus) and parietal (e.g., postcentral gyrus) regions. Furthermore, the altered topological metrics (e.g., increased global efficiency and reduced nodal efficiency) were correlated with the severity of ASD symptoms. CONCLUSION These results indicated that the complicatedly topological organization of the white matter structural network was abnormal and may play an essential role in the underlying pathological mechanism of ASD in adults.
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Affiliation(s)
- Yun Cai
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Jinghui Zhao
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Lian Wang
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Yuanjun Xie
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710030, China.
| | - Xiaotang Fan
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China.
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Lin YJ, Chiu YN, Wu YY, Tsai WC, Gau SSF. Developmental Changes of Autistic Symptoms, ADHD Symptoms, and Attentional Performance in Children and Adolescents with Autism Spectrum Disorder. J Autism Dev Disord 2022:10.1007/s10803-022-05445-x. [PMID: 35420295 DOI: 10.1007/s10803-022-05445-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2022] [Indexed: 12/01/2022]
Abstract
This study followed up ADHD/autistic symptoms and attentional performance in children/adolescents with ASD and typically developing ones (TD) over 5-7 years. The participants were stratified by age at baseline into child (< 12 years) and adolescent (12-19 years) groups. ADHD symptoms, especially hyperactivity, and attentional functions significantly improved during follow-up, more in children than in adolescents, in both ASD and TD. Significantly more omission errors and perseverations were noted in ASD than TD through the follow-up. Children with ASD had more improvement in reaction time while adolescents with ASD had less improvement in commission errors and detectability than TD. No correlation of attentional functions and ADHD symptoms in ASD implied different neural mechanisms of ADHD symptoms between ASD and ADHD.
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Affiliation(s)
- Yu-Ju Lin
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan.,Department of Psychiatry, Far Eastern Memorial Hospital, New Taipei City, Taiwan
| | - Yen-Nan Chiu
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan
| | - Yu-Yu Wu
- YuNing Psychiatry Clinic, Taipei, Taiwan
| | - Wen-Che Tsai
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan. .,Department of Psychology, Graduate Institute of Epidemiology, and Preventive Medicine, and Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan.
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Hiramoto T, Sumiyoshi A, Yamauchi T, Tanigaki K, Shi Q, Kang G, Ryoke R, Nonaka H, Enomoto S, Izumi T, Bhat MA, Kawashima R, Hiroi N. Tbx1, a gene encoded in 22q11.2 copy number variant, is a link between alterations in fimbria myelination and cognitive speed in mice. Mol Psychiatry 2022; 27:929-938. [PMID: 34737458 PMCID: PMC9054676 DOI: 10.1038/s41380-021-01318-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 09/15/2021] [Accepted: 09/23/2021] [Indexed: 12/18/2022]
Abstract
Copy number variants (CNVs) have provided a reliable entry point to identify the structural correlates of atypical cognitive development. Hemizygous deletion of human chromosome 22q11.2 is associated with impaired cognitive function; however, the mechanisms by which the CNVs contribute to cognitive deficits via diverse structural alterations in the brain remain unclear. This study aimed to determine the cellular basis of the link between alterations in brain structure and cognitive functions in mice with a heterozygous deletion of Tbx1, one of the 22q11.2-encoded genes. Ex vivo whole-brain diffusion-tensor imaging (DTI)-magnetic resonance imaging (MRI) in Tbx1 heterozygous mice indicated that the fimbria was the only region with significant myelin alteration. Electron microscopic and histological analyses showed that Tbx1 heterozygous mice exhibited an apparent absence of large myelinated axons and thicker myelin in medium axons in the fimbria, resulting in an overall decrease in myelin. The fimbria of Tbx1 heterozygous mice showed reduced mRNA levels of Ng2, a gene required to produce oligodendrocyte precursor cells. Moreover, postnatal progenitor cells derived from the subventricular zone, a source of oligodendrocytes in the fimbria, produced fewer oligodendrocytes in vitro. Behavioral analyses of these mice showed selectively slower acquisition of spatial memory and cognitive flexibility with no effects on their accuracy or sensory or motor capacities. Our findings provide a genetic and cellular basis for the compromised cognitive speed in patients with 22q11.2 hemizygous deletion.
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Affiliation(s)
- Takeshi Hiramoto
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Akira Sumiyoshi
- Institute of Development, Aging, and Cancer, Tohoku University, 4-1, Seiryo-cho, Aoba-ku, Sendai, 980-8575, Japan
- National Institutes for Quantum and Radiological Science and Technology, 4-9-1, Anagawa, Inage-ku, Chiba, 263-8555, Japan
| | - Takahira Yamauchi
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Kenji Tanigaki
- Research Institute, Shiga Medical Center, 5-4-30 Moriyama, Moriyama-shi, Shiga, Japan
| | - Qian Shi
- Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Gina Kang
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Rie Ryoke
- Institute of Development, Aging, and Cancer, Tohoku University, 4-1, Seiryo-cho, Aoba-ku, Sendai, 980-8575, Japan
| | - Hiroi Nonaka
- Institute of Development, Aging, and Cancer, Tohoku University, 4-1, Seiryo-cho, Aoba-ku, Sendai, 980-8575, Japan
| | - Shingo Enomoto
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, 10461, USA
| | - Takeshi Izumi
- Department of Pharmacology, Health Sciences University of Hokkaido, 1757 Kanazawa, Tobetsu, Ishikari, Hokkaido, 061-0293, Japan
- Advanced Research Promotion Center, Health Sciences University of Hokkaido, 1757 Kanazawa, Tobetsu, Ishikari, Hokkaido, 061-0293, Japan
| | - Manzoor A Bhat
- Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA
| | - Ryuta Kawashima
- Institute of Development, Aging, and Cancer, Tohoku University, 4-1, Seiryo-cho, Aoba-ku, Sendai, 980-8575, Japan
| | - Noboru Hiroi
- Department of Pharmacology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.
- Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.
- Department of Cell Systems and Anatomy, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.
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Children with Autism Spectrum Disorder of All Ages, Levels of Symptom Severity and General Cognitive Ability Display Low Processing Speed Index Scores Warranting Special Educational Assistance. J Autism Dev Disord 2021; 52:3668-3675. [PMID: 34453226 PMCID: PMC9296421 DOI: 10.1007/s10803-021-05249-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/19/2021] [Indexed: 11/17/2022]
Abstract
The processing speed index (PSI) of the Wechsler intelligence scale for children (WISC-IV) has been found to predict a child's level of academic functioning. The consistently reported PSI weakness in children with autism spectrum disorder (ASD) therefore warrants special assistance and attempts at compensation for the disadvantages associated with these children's low PSI. We investigated the association of PSI scores with age, general cognitive ability [as measured by full-scale IQ (FSIQ)], symptom severity and discrepancy between the WISC-IV indices verbal comprehension (VCI) and perceptual reasoning (PRI) in 101 school children with ASD. The PSI weakness in children with ASD was not related to age, FSIQ, VCI-PRI discrepancy or any of the symptom measures. These findings suggest that school children with ASD independent of their age, level of cognitive ability, VCI-PRI profile and most notably independent of their symptom severity should be entitled to special assistance and compensation in educational settings.
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10
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Clinical Utility of the Patient Health Questionnaire–Adolescent in Adolescents With Traumatic Brain Injury. J Head Trauma Rehabil 2020; 36:E118-E125. [DOI: 10.1097/htr.0000000000000610] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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11
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Gosar D, Tretnjak V, Bregant T, Neubauer D, Derganc M. Reduced white-matter integrity and lower speed of information processing in adolescents with mild and moderate neonatal hypoxic-ischaemic encephalopathy. Eur J Paediatr Neurol 2020; 28:205-213. [PMID: 32665198 DOI: 10.1016/j.ejpn.2020.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 06/07/2020] [Accepted: 06/08/2020] [Indexed: 01/21/2023]
Abstract
INTRODUCTION Studies have shown that adolescents with moderate hypoxic-ischaemic encephalopathy (HIE) may have specific cognitive deficits, especially reduced speed of information processing. The aim of our study was to confirm these earlier findings find out whether the degree of impairment in speed of information processing correlates with the degree of white-matter impairment as measured by diffusion tensor imaging (DTI). METHODS Thirty-three participants (mean age 18y 5mo, SD 12mo; 19 male) with mild or moderate HIE and 32 neurotypical adolescents (mean age 17y 10mo, SD 12mo, 18 male) completed a comprehensive neuropsychological battery measuring short-term memory, inhibition, speed of information processing, long-term visual and verbal memory. Fourteen participants also underwent structural MRI and DTI scans. RESULTS After controlling for age, gender and maternal education we found a significant effect of HIE on speed of information processing (F(2, 64) = 3.51, p < .037, η2 = 0.115), but not on other neuropsychological domains. Using tract-based spatial statistics we were also able to confirm a correlation between the degree of impairment in this cognitive domain and fractional anisotropy in several white-matter tracts. CONCLUSIONS The long-term cognitive outcome of moderate HIE includes reduced speed of information processing and is in part mediated by reduced integrity of major white-matter tracts.
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Affiliation(s)
- David Gosar
- University Children's Hospital, University Medical Centre Ljubljana, Department of Child, Adolescent and Developmental Neurology, Ljubljana, Slovenia.
| | - Vali Tretnjak
- University Children's Hospital, University Medical Centre Ljubljana, Department of Child, Adolescent and Developmental Neurology, Ljubljana, Slovenia
| | - Tina Bregant
- Centre for Education and Rehabilitation of Physically Handicapped Children and Adolescents - CIRIUS Kamnik, Slovenia
| | - David Neubauer
- University Children's Hospital, University Medical Centre Ljubljana, Department of Child, Adolescent and Developmental Neurology, Ljubljana, Slovenia
| | - Metka Derganc
- University Medical Centre Ljubljana, Department of Paediatric Surgery and Intensive Care, Ljubljana, Slovenia
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12
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Ola L, Gullon-Scott F. Facial emotion recognition in autistic adult females correlates with alexithymia, not autism. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2020; 24:2021-2034. [PMID: 32689812 PMCID: PMC7539601 DOI: 10.1177/1362361320932727] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Research on predominantly male autistic samples has indicated that impairments in facial emotion recognition typically associated with autism spectrum conditions are instead due to co-occurring alexithymia. However, whether this could be demonstrated using more realistic facial emotion recognition stimuli and applied to autistic females was unclear. In all, 83 females diagnosed with autism spectrum condition completed online self-report measures of autism spectrum condition severity and alexithymia, and afacial emotion recognition deficit that assessed their ability to identify multimodal displays of complex emotions. Higher levels of alexithymia, but not autism spectrum condition severity, were associated with less accurate facial emotion recognition. Difficulty identifying one’s own feelings and externally oriented thinking were the components of alexithymia that were specifically related to facial emotion recognition accuracy. However, alexithymia (and autism spectrum condition severity) was not associated with speed of emotion processing. The findings are primarily discussed with the theoretical view that perceiving and experiencing emotions share the same neural networks, thus being able to recognise one’s own emotions may facilitate the ability to recognise others’. This study is in line with previous similar research on autistic males and suggests impairments in facial emotion recognition in autistic females should be attributed to co-occurring alexithymia.
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13
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Kramer E, Koo B, Restrepo A, Koyama M, Neuhaus R, Pugh K, Andreotti C, Milham M. Diagnostic Associations of Processing Speed in a Transdiagnostic, Pediatric Sample. Sci Rep 2020; 10:10114. [PMID: 32572148 PMCID: PMC7308370 DOI: 10.1038/s41598-020-66892-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 05/15/2020] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION The present study examines the relationships between processing speed (PS), mental health disorders, and learning disorders. Prior work has tended to explore relationships between PS deficits and specific diagnoses in isolation of one another. Here, we simultaneously investigated PS associations with five diagnoses (i.e., anxiety, autism, ADHD, depressive, specific learning) in a large-scale, transdiagnostic, community self-referred sample. METHOD 843 children, ages 8-16 were included from the Healthy Brain Network (HBN) Biobank. Principal component analysis (PCA) was employed to create a composite measure of four PS tasks, referred to as PC1. Intraclass correlation coefficient (ICC) between the four PS measures, as well as PC1, were calculated to assess reliability. RESULTS ICCs were moderate between WISC-V tasks (0.663), and relatively modest between NIH Toolbox Pattern Comparison and other PS scales (0.14-0.27). Regression analyses revealed specific significant relationships between PS and reading and math disabilities, ADHD-inattentive presentation (ADHD-I), and ADHD-combined presentation (ADHD-C). After accounting for inattention, the present study did not find a significant relationship with Autism Spectrum Disorder. DISCUSSION Our examination of PS in a large, transdiagnostic sample suggested more specific associations with ADHD and learning disorders than the literature currently suggests. Implications for understanding how PS interacts with a highly heterogeneous childhood sample are discussed.
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Affiliation(s)
- Eliza Kramer
- Healthy Brain Network, Child Mind Institute, New York, New York, USA
| | - Bonhwang Koo
- Center for the Developing Brain, Child Mind Institute, New York, New York, USA
| | - Anita Restrepo
- Healthy Brain Network, Child Mind Institute, New York, New York, USA
| | | | - Rebecca Neuhaus
- Healthy Brain Network, Child Mind Institute, New York, New York, USA
| | | | | | - Michael Milham
- Center for the Developing Brain, Child Mind Institute, New York, New York, USA.
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA.
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14
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Peled J, Cassuto H, Berger I. Processing speed as a marker to stimulant effect in clinical sample of children with high functioning autism spectrum disorder. Nord J Psychiatry 2020; 74:163-167. [PMID: 31686565 DOI: 10.1080/08039488.2019.1686063] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Background: Patients with co-occurring Attention-Deficit/Hyperactivity Disorder (ADHD) and ASD might benefit from stimulants. There is a progressive increase in prescribing ADHD aimed medications for children diagnosed with Autism Spectrum Disorder (ASD), despite scarce knowledge and no distinct clinical guidelines for that matter.Aim: This study aims to analyze the effect of stimulant on processing speed performance and attention indices in children with ASD and ADHD.Methods: Forty children aged 6-18 years diagnosed with ASD who also met the criteria for ADHD were recruited. All children performed a computerized performance test for the assessment of cognitive attention performance three times: twice while they are drug naïve and once an hour after taking a single dose of 10 mg. methylphenidate (MPH). This performance was compared to a group of children diagnosed with 'ADHD only' without ASD.Results: A significant difference (p < 0.001) was found only in the parameter of measuring cognitive processing speed. This effect is significantly different from the response of the 'ADHD only' group.Conclusions: The reaction to MPH among ASD children is different than among ADHD children. In ASD, MPH significantly improved cognitive processing speed without changing other measured attention parameters. Improving processing speed, might improve every day functioning in children with ASD who also met the criteria for ADHD, in other means than expected. This unique response suggests new research targets for treatment with stimulants in ASD and ADHD children and its influence on cognitive parameters.
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Affiliation(s)
- Julia Peled
- The Hebrew University-Hadassah Medical School, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.,Kaplan Medical Center, Rehovot, Israel
| | - Hanoch Cassuto
- Pediatric Neurology Clinics, Leumit HMO, Jerusalem, Israel
| | - Itai Berger
- Pediatric Neurology, Assuta-Ashdod University Medical Center, The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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15
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Haigh SM, Keller TA, Minshew NJ, Eack SM. Reduced White Matter Integrity and Deficits in Neuropsychological Functioning in Adults With Autism Spectrum Disorder. Autism Res 2020; 13:702-714. [PMID: 32073209 DOI: 10.1002/aur.2271] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 12/06/2019] [Accepted: 01/15/2020] [Indexed: 12/31/2022]
Abstract
Autism spectrum disorder (ASD) is currently viewed as a disorder of cortical systems connectivity, with a heavy emphasis being on the structural integrity of white matter tracts. However, the majority of the literature to date has focused on children with ASD. Understanding the integrity of white matter tracts in adults may help reveal the nature of ASD pathology in adulthood and the potential contributors to cognitive impairment. This study examined white matter water diffusion using diffusion tensor imaging in relation to neuropsychological measures of cognition in a sample of 45 adults with ASD compared to 20 age, gender, and full-scale-IQ-matched healthy volunteers. Tract-based spatial statistics were used to assess differences in diffusion along white matter tracts between groups using permutation testing. The following neuropsychological measures of cognition were assessed: processing speed, attention vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Results indicated that fractional anisotropy (FA) was significantly reduced in adults with ASD in the anterior thalamic radiation (P = 0.022) and the right cingulum (P = 0.008). All neuropsychological measures were worse in the ASD group, but none of the measures significantly correlated with reduced FA in either tract in the adults with ASD or in the healthy volunteers. Together, this indicates that the tracts that are the most impacted in autism may not be (at least directly) responsible for the behavioral deficits in ASD. Autism Res 2020, 13: 702-714. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: White matter tracts are the data cables in the brain that efficiently transfer information, and damage to these tracts could be the cause for the abnormal behaviors that are associated with autism. We found that two long-range tracts (the anterior thalamic radiation and the cingulum) were both impaired in autism but were not directly related to the impairments in behavior. This suggests that the abnormal tracts and behavior are the effects of another underlying mechanism.
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Affiliation(s)
- Sarah M Haigh
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania.,Department of Psychology and Integrative Neuroscience, University of Nevada, Reno, Nevada
| | - Timothy A Keller
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Nancy J Minshew
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Shaun M Eack
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.,School of Social Work, University of Pittsburgh, Pittsburgh, Pennsylvania
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16
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Kuo SS, Eack SM. Meta-Analysis of Cognitive Performance in Neurodevelopmental Disorders during Adulthood: Comparisons between Autism Spectrum Disorder and Schizophrenia on the Wechsler Adult Intelligence Scales. Front Psychiatry 2020; 11:187. [PMID: 32273855 PMCID: PMC7114889 DOI: 10.3389/fpsyt.2020.00187] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 02/26/2020] [Indexed: 11/13/2022] Open
Abstract
Autism Spectrum Disorder (ASD) and schizophrenia are neurodevelopmental disorders which show substantial cognitive heterogeneity in adulthood, yet it remains unclear whether cognitive profiles may overlap across these diagnoses. Thus, the aim of this review was to summarize comparisons between ASD and schizophrenia on nonsocial cognition in adulthood. To minimize between-study heterogeneity in a relatively small literature, subtest scaled scores from the Wechsler Adult Intelligence Scale were compared between ASD (N=190) and schizophrenia (N=260) in six studies comprising a total of 450 participants. Meta-analyses of 11 subtests indicated that participants with ASD demonstrated significantly better performance than schizophrenia for visuospatial perception and reasoning and problem solving (Hedge's g=0.636), as well as visual attention and organization (g=0.433-0.475). Participants with ASD also demonstrated better performance than those with schizophrenia for working memory (g=0.334) and language (g=0.275), and generally comparable performance on processing speed and verbal comprehension. These findings were largely stable across age, sex, intelligence quotient (IQ), intellectual disability, scale version, and age- and sex-matching. Overall, ASD and schizophrenia showed striking differences in visuospatial perception and reasoning and problem solving, small differences in working memory and language, and substantial overlap in processing speed and verbal comprehension. These cognitive profiles were generally stable from adolescence to middle adulthood. To our knowledge, this is the first review to summarize comparisons of nonsocial cognition in verbal adults with ASD or schizophrenia. These findings are consistent with and substantially extend prior meta-analyses of case-control studies for ASD and schizophrenia (8, 9), which also suggest that, in comparison to neurotypical controls, ASD demonstrates smaller cognitive impairments than schizophrenia across most cognitive domains, particularly working memory, visuospatial learning/memory, and language. Our findings therefore highlight the importance of comparing cognition transdiagnostically to inform the etiologies of these neurodevelopmental disorders and to refine shared and unique targets for remediating cognition.
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Affiliation(s)
- Susan S Kuo
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Shaun M Eack
- School of Social Work and Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
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17
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Yuk V, Urbain C, Anagnostou E, Taylor MJ. Frontoparietal Network Connectivity During an N-Back Task in Adults With Autism Spectrum Disorder. Front Psychiatry 2020; 11:551808. [PMID: 33033481 PMCID: PMC7509600 DOI: 10.3389/fpsyt.2020.551808] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 08/13/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Short-term and working memory (STM and WM) deficits have been demonstrated in individuals with autism spectrum disorder (ASD) and may emerge through atypical functional activity and connectivity of the frontoparietal network, which exerts top-down control necessary for successful STM and WM processes. Little is known regarding the spectral properties of the frontoparietal network during STM or WM processes in ASD, although certain neural frequencies have been linked to specific neural mechanisms. METHODS We analysed magnetoencephalographic data from 39 control adults (26 males; 27.15 ± 5.91 years old) and 40 adults with ASD (26 males; 27.17 ± 6.27 years old) during a 1-back condition (STM) of an n-back task, and from a subset of this sample during a 2-back condition (WM). We performed seed-based connectivity analyses using regions of the frontoparietal network. Interregional synchrony in theta, alpha, and beta bands was assessed with the phase difference derivative and compared between groups during periods of maintenance and recognition. RESULTS During maintenance of newly presented vs. repeated stimuli, the two groups did not differ significantly in theta, alpha, or beta phase synchrony for either condition. Adults with ASD showed alpha-band synchrony in a network containing the right dorsolateral prefrontal cortex, bilateral inferior parietal lobules (IPL), and precuneus in both 1- and 2-back tasks, whereas controls demonstrated alpha-band synchrony in a sparser set of regions, including the left insula and IPL, in only the 1-back task. During recognition of repeated vs. newly presented stimuli, adults with ASD exhibited decreased theta-band connectivity compared to controls in a network with hubs in the right inferior frontal gyrus and left IPL in the 1-back condition. Whilst there were no group differences in connectivity in the 2-back condition, adults with ASD showed no frontoparietal network recruitment during recognition, whilst controls activated networks in the theta and beta bands. CONCLUSIONS Our findings suggest that since adults with ASD performed well on the n-back task, their appropriate, but effortful recruitment of alpha-band mechanisms in the frontoparietal network to maintain items in STM and WM may compensate for atypical modulation of this network in the theta band to recognise previously presented items in STM.
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Affiliation(s)
- Veronica Yuk
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.,Neurosciences & Mental Health Program, SickKids Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Charline Urbain
- Neuropsychology and Functional Neuroimaging Research Group, Center for Research in Cognition & Neurosciences and ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.,Laboratoire de Cartographie Fonctionnelle du Cerveau, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada.,Department of Neurology, The Hospital for Sick Children, Toronto, ON, Canada.,Department of Paediatrics, University of Toronto, Toronto, ON, Canada
| | - Margot J Taylor
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.,Neurosciences & Mental Health Program, SickKids Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.,Department of Psychology, University of Toronto, Toronto, ON, Canada.,Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
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18
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Raatikainen V, Korhonen V, Borchardt V, Huotari N, Helakari H, Kananen J, Raitamaa L, Joskitt L, Loukusa S, Hurtig T, Ebeling H, Uddin LQ, Kiviniemi V. Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder. Autism Res 2019; 13:244-258. [PMID: 31637863 PMCID: PMC7027814 DOI: 10.1002/aur.2218] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 08/28/2019] [Accepted: 09/16/2019] [Indexed: 02/06/2023]
Abstract
This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244–258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. Lay Summary Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra‐fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default‐mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder.
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Affiliation(s)
- Ville Raatikainen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Viola Borchardt
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Niko Huotari
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Heta Helakari
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Janne Kananen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Lauri Raitamaa
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Leena Joskitt
- Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Soile Loukusa
- Research Unit of Logopedics, Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Tuula Hurtig
- Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Hanna Ebeling
- Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, Florida
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
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19
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King JB, Prigge MBD, King CK, Morgan J, Dean DC, Freeman A, Villaruz JAM, Kane KL, Bigler ED, Alexander AL, Lange N, Zielinski BA, Lainhart JE, Anderson JS. Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development. JAMA Netw Open 2018; 1:e184777. [PMID: 30646371 PMCID: PMC6324391 DOI: 10.1001/jamanetworkopen.2018.4777] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
IMPORTANCE Despite reports of widespread but heterogeneous atypicality of functional connectivity in individuals with autism, little is known regarding the temporal dynamics of functional brain connections and how they relate to autistic traits. OBJECTIVE To investigate differences in temporal synchrony between brain regions in individuals with autism and those with typical development. DESIGN, SETTING, AND PARTICIPANTS This cohort study, conducted at the University of Utah, included 90 adolescent and adult male participants. A larger sample from the multisite Autism Brain Imaging Data Exchange (ABIDE) was also used as a replication sample. The study includes data acquired between December 2016 and April 2018. Aggregate data included in the replication sample were released to the public in August 2012 (ABIDE I) and June 2016 (ABIDE II). Data analysis were conducted between January 2018 and April 2018. EXPOSURES Male individuals diagnosed as having autism (n = 52) and typically developing male individuals (n = 38). MAIN OUTCOMES AND MEASURES Long duration (30 minutes/individual) of multiband, multiecho functional magnetic resonance imaging was acquired to estimate functional connectivity between brain regions. Sustained connectivity, a measure of functional connectivity duration, as well as lagged temporal dynamics related to functional connectivity, were compared between groups for 361 gray matter regions of interest and a 17-network parcellation. Lagged findings were replicated in the larger ABIDE sample (n = 1402). Sustained connectivity findings were also associated with behavioral and cognitive variables. RESULTS In 52 males with autism (mean [SD] age, 27.73 [8.66] years) and 38 control males with typical development (mean [SD] age, 27.09 [7.49] years), increases in both sustained and functional connectivity at several lags were found in individuals with autism compared with the control group. Group differences in functional connectivity were replicated in the larger ABIDE data set at a 6-second lag. Measures of symptom severity in individuals with autism were positively associated with sustained connectivity values. In the control group, sustained connectivity was negatively associated with cognitive processing. A replication sample (n = 1402) composed of 579 individuals with autism (80 female and 499 male; mean [SD] age, 15.08 [6.89] years) and 823 in the control group (211 female and 612 male; mean [SD] age, 15.06 [6.79] years) from the ABIDE data set was also analyzed. CONCLUSIONS AND RELEVANCE Whereas the magnitude of functional connectivity in autism is variable across brain regions, participant samples, and development, prolonged temporal synchrony of functional connections is reproducibly observed in autism, suggesting a potential mechanism for core symptoms.
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Affiliation(s)
- Jace B. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City
| | - Molly B. D. Prigge
- Department of Pediatrics, University of Utah, Salt Lake City
- Waisman Center, University of Wisconsin–Madison, Madison
| | - Carolyn K. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City
- Department of Pediatrics, University of Utah, Salt Lake City
| | - Jubel Morgan
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City
- Department of Pediatrics, University of Utah, Salt Lake City
- Waisman Center, University of Wisconsin–Madison, Madison
| | | | - Abigail Freeman
- Waisman Center, University of Wisconsin–Madison, Madison
- Department of Psychiatry, University of Wisconsin–Madison, Madison
| | | | - Karen L. Kane
- Waisman Center, University of Wisconsin–Madison, Madison
- Department of Psychiatry, University of Wisconsin–Madison, Madison
| | - Erin D. Bigler
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, Utah
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin–Madison, Madison
- Department of Psychiatry, University of Wisconsin–Madison, Madison
- Department of Medical Physics, University of Wisconsin–Madison, Madison
| | - Nicholas Lange
- McLean Hospital and Department of Psychiatry, Harvard University, Cambridge, Massachusetts
| | - Brandon A. Zielinski
- Department of Pediatrics, University of Utah, Salt Lake City
- Department of Neurology, University of Utah, Salt Lake City
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin–Madison, Madison
- Department of Psychiatry, University of Wisconsin–Madison, Madison
| | - Jeffrey S. Anderson
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City
- Department of Bioengineering, University of Utah, Salt Lake City
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20
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Ocak E, Eshraghi RS, Danesh A, Mittal R, Eshraghi AA. Central Auditory Processing Disorders in Individuals with Autism Spectrum Disorders. Balkan Med J 2018; 35:367-372. [PMID: 29952312 PMCID: PMC6158468 DOI: 10.4274/balkanmedj.2018.0853] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
The etiology and the underlying pathogenetic mechanisms of autism spectrum disorders are still largely unknown. This article provides a comprehensive review of the studies that are relevant to autism spectrum disorders and central auditory processing disorders and also discusses the relationship between autism spectrum disorders and central auditory processing disorders in the light of recent studies on this subject, which may provide new pathways in a therapeutic perspective. Several studies confirm that most of the individuals with an autism spectrum disorder have some degree of sensory dysfunction related to disorders of processing auditory, visual, vestibular, and/or tactile stimuli. Among these studies, some have addressed central auditory processing disorders. There is an increasing amount of effort for studies regarding the link between autism spectrum disorders and central auditory processing disorders. Most of the studies investigating central auditory processing disorders in patients with autism spectrum disorders have used electrophysiological measurements such as mismatch negativity and P300 event-related potentials. In addition to these, several studies have reported deterioration in speech perception and expression in patients with autism spectrum disorders, which may also be related to central auditory processing disorders in this unique group of individuals.
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Affiliation(s)
- Emre Ocak
- Department of Otolaryngology and Neurological Surgery, University of Miami Miller School of Medicine, Miami, USA
| | - Rebecca S. Eshraghi
- Department of Gastroenterology, University of Miami Miller School of Medicine, Miami USA
| | - Ali Danesh
- Department of Audiology, Florida Atlantic University School of Medicine, Miami, USA
| | - Rahul Mittal
- Department of Otolaryngology and Neurological Surgery, University of Miami Miller School of Medicine, Miami, USA
| | - Adrien A. Eshraghi
- Department of Otolaryngology and Neurological Surgery, University of Miami Miller School of Medicine, Miami, USA
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21
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Neuromotor and cognitive responses of adults with autism spectrum disorder compared to neurotypical adults. Exp Brain Res 2018; 236:2321-2332. [DOI: 10.1007/s00221-018-5300-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 05/24/2018] [Indexed: 10/14/2022]
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22
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Powell PS, Klinger LG, Klinger MR. Patterns of Age-Related Cognitive Differences in Adults with Autism Spectrum Disorder. J Autism Dev Disord 2018; 47:3204-3219. [PMID: 28730417 DOI: 10.1007/s10803-017-3238-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Little is known about age-related cognitive differences in autism spectrum disorder (ASD). However, given the overlap in cognitive impairments in ASD to those seen in typical aging, it is possible that adults with ASD will face even greater cognitive difficulties as they age. The current study used a cross-sectional design to examine age-related cognitive differences in adults with ASD and age and IQ-matched adults with typical development (age range 30-67 years). Results indicated that both age and diagnosis were related to poorer cognitive performance. However, adults with ASD exhibited pronounced age effects on measures related to executive functioning compared to adults with typical development, suggesting that aging in ASD may disproportionately affect specific cognitive processes.
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Affiliation(s)
- Patrick S Powell
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street NW, Atlanta, GA, 30332-0170, USA.
| | - Laura G Klinger
- TEACCH Autism Program, Department of Psychiatry, University of North Carolina - Chapel Hill, 100 Renee Lynne Court, Chapel Hill, NC, 27599-7180, USA
| | - Mark R Klinger
- Department of Allied Health Sciences, University of North Carolina - Chapel Hill, 321 S Columbia St., Chapel Hill, NC, 27514, USA
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23
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Bednarz HM, Kana RK. Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders. Neurosci Biobehav Rev 2018; 90:50-69. [PMID: 29608989 DOI: 10.1016/j.neubiorev.2018.03.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 02/26/2018] [Accepted: 03/22/2018] [Indexed: 10/17/2022]
Abstract
Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.
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Affiliation(s)
- Haley M Bednarz
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rajesh K Kana
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
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24
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Martínez K, Merchán-Naranjo J, Pina-Camacho L, Alemán-Gómez Y, Boada L, Fraguas D, Moreno C, Arango C, Janssen J, Parellada M. Atypical age-dependency of executive function and white matter microstructure in children and adolescents with autism spectrum disorders. Eur Child Adolesc Psychiatry 2017; 26:1361-1376. [PMID: 28447268 DOI: 10.1007/s00787-017-0990-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 04/17/2017] [Indexed: 11/29/2022]
Abstract
Executive function (EF) performance is associated with measurements of white matter microstructure (WMS) in typical individuals. Impaired EF is a hallmark symptom of autism spectrum disorders (ASD) but it is unclear how impaired EF relates to variability in WMS. Twenty-one male youth (8-18 years) with ASD and without intellectual disability and twenty-one typical male participants (TP) matched for age, intelligence quotient, handedness, race and parental socioeconomic status were recruited. Five EF domains were assessed and several DTI-based measurements of WMS [fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD)] were estimated for eighteen white matter tracts. The ASD group had lower scores for attention (F = 8.37, p = 0.006) and response inhibition (F = 13.09, p = 0.001). Age-dependent changes of EF performance and WMS measurements were present in TP but attenuated in the ASD group. The strongest diagnosis-by-age effect was found for forceps minor, left anterior thalamic radiation and left cingulum angular bundle (all p's ≤ 0.002). In these tracts subjects with ASD tended to have equal or increased FA and/or reduced MD and/or RD at younger ages while controls had increased FA and/or reduced MD and/or RD thereafter. Only for TP individuals, increased FA in the left anterior thalamic radiation was associated with better response inhibition, while reduced RD in forceps minor and left cingulum angular bundle was related to better problem solving and working memory performance respectively. These findings provide novel insight into the age-dependency of EF performance and WMS in ASD, which can be instructive to cognitive training programs.
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Affiliation(s)
- Kenia Martínez
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain. .,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain. .,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain. .,Universidad Europea de Madrid, Madrid, Spain. .,Hospital Gregorio Marañón, Edificio prefabricado, entrada por Máiquez 9, 28009, Madrid, Spain.
| | - Jessica Merchán-Naranjo
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Laura Pina-Camacho
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Yasser Alemán-Gómez
- Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Leticia Boada
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - David Fraguas
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Carmen Moreno
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Universidad Complutense de Madrid, Madrid, Spain
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mara Parellada
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Universidad Complutense de Madrid, Madrid, Spain
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25
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Demopoulos C, Yu N, Tripp J, Mota N, Brandes-Aitken AN, Desai SS, Hill SS, Antovich AD, Harris J, Honma S, Mizuiri D, Nagarajan SS, Marco EJ. Magnetoencephalographic Imaging of Auditory and Somatosensory Cortical Responses in Children with Autism and Sensory Processing Dysfunction. Front Hum Neurosci 2017; 11:259. [PMID: 28603492 PMCID: PMC5445128 DOI: 10.3389/fnhum.2017.00259] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2017] [Accepted: 05/01/2017] [Indexed: 11/25/2022] Open
Abstract
This study compared magnetoencephalographic (MEG) imaging-derived indices of auditory and somatosensory cortical processing in children aged 8–12 years with autism spectrum disorder (ASD; N = 18), those with sensory processing dysfunction (SPD; N = 13) who do not meet ASD criteria, and typically developing control (TDC; N = 19) participants. The magnitude of responses to both auditory and tactile stimulation was comparable across all three groups; however, the M200 latency response from the left auditory cortex was significantly delayed in the ASD group relative to both the TDC and SPD groups, whereas the somatosensory response of the ASD group was only delayed relative to TDC participants. The SPD group did not significantly differ from either group in terms of somatosensory latency, suggesting that participants with SPD may have an intermediate phenotype between ASD and TDC with regard to somatosensory processing. For the ASD group, correlation analyses indicated that the left M200 latency delay was significantly associated with performance on the WISC-IV Verbal Comprehension Index as well as the DSTP Acoustic-Linguistic index. Further, these cortical auditory response delays were not associated with somatosensory cortical response delays or cognitive processing speed in the ASD group, suggesting that auditory delays in ASD are domain specific rather than associated with generalized processing delays. The specificity of these auditory delays to the ASD group, in addition to their correlation with verbal abilities, suggests that auditory sensory dysfunction may be implicated in communication symptoms in ASD, motivating further research aimed at understanding the impact of sensory dysfunction on the developing brain.
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Affiliation(s)
- Carly Demopoulos
- Department of Radiology, University of California, San FranciscoSan Francisco, CA, United States
| | - Nina Yu
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Jennifer Tripp
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Nayara Mota
- Department of Radiology, University of California, San FranciscoSan Francisco, CA, United States
| | - Anne N Brandes-Aitken
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Shivani S Desai
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Susanna S Hill
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Ashley D Antovich
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Julia Harris
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States
| | - Susanne Honma
- Department of Radiology, University of California, San FranciscoSan Francisco, CA, United States
| | - Danielle Mizuiri
- Department of Radiology, University of California, San FranciscoSan Francisco, CA, United States
| | - Srikantan S Nagarajan
- Department of Radiology, University of California, San FranciscoSan Francisco, CA, United States
| | - Elysa J Marco
- Department of Neurology, University of California, San FranciscoSan Francisco, CA, United States.,Department of Pediatrics, University of California, San FranciscoSan Francisco, CA, United States.,Department of Psychiatry, University of California, San FranciscoSan Francisco, CA, United States
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26
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Lundwall RA, Stephenson KG, Neeley-Tass ES, Cox JC, South M, Bigler ED, Anderberg E, Prigge MD, Hansen BD, Lainhart JE, Kellems RO, Petrie JA, Gabrielsen TP. Relationship between brain stem volume and aggression in children diagnosed with autism spectrum disorder. RESEARCH IN AUTISM SPECTRUM DISORDERS 2017; 34:44-51. [PMID: 28966659 PMCID: PMC5617125 DOI: 10.1016/j.rasd.2016.12.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
BACKGROUND Aggressive behaviors are common in individuals diagnosed with autism spectrum disorder (ASD) and may be phenotypic indicators of different subtypes within ASD. In current research literature for non-ASD samples, aggression has been linked to several brain structures associated with emotion and behavioral control. However, few if any studies exist investigating brain volume differences in individuals with ASD who have comorbid aggression as indicated by standardized diagnostic and behavioral measures. METHOD We examined neuroimaging data from individuals rigorously diagnosed with ASD versus typically developing (TD) controls. We began with data from brain volume regions of interest (ROI) taken from previous literature on aggression including the brainstem, amygdala, orbitofrontal cortex, anterior cingulate cortex, and dorsolateral prefrontal cortex. We defined aggression status using the Irritability subscale of the Aberrant Behavior Checklist and used lasso logistic regression to select among these predictor variables. Brainstem volume was the only variable shown to be a predictor of aggression status. RESULTS We found that smaller brainstem volumes are associated with higher odds of being in the high aggression group. CONCLUSIONS Understanding brain differences in individuals with ASD who engage in aggressive behavior from those with ASD who do not can inform treatment approaches. Future research should investigate brainstem structure and function in ASD to identify possible mechanisms related to arousal and aggression.
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Affiliation(s)
| | | | | | | | - Mikle South
- Brigham Young University, Provo, UT 84602, USA
| | | | | | - Molly D Prigge
- University of Utah, 201 Presidents Circle, SLC, UT 84112, USA
| | - Blake D Hansen
- University of Utah, 201 Presidents Circle, SLC, UT 84112, USA
| | - Janet E Lainhart
- University of Wisconsin-Madison, 500 Lincoln Drive, Madison, WI 53706, USA
| | - Ryan O Kellems
- University of Wisconsin-Madison, 500 Lincoln Drive, Madison, WI 53706, USA
| | - Jo Ann Petrie
- University of Wisconsin-Madison, 500 Lincoln Drive, Madison, WI 53706, USA
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27
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Dean DC, Lange N, Travers BG, Prigge MB, Matsunami N, Kellett KA, Freeman A, Kane KL, Adluru N, Tromp DPM, Destiche DJ, Samsin D, Zielinski BA, Fletcher PT, Anderson JS, Froehlich AL, Leppert MF, Bigler ED, Lainhart JE, Alexander AL. Multivariate characterization of white matter heterogeneity in autism spectrum disorder. Neuroimage Clin 2017; 14:54-66. [PMID: 28138427 PMCID: PMC5257193 DOI: 10.1016/j.nicl.2017.01.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 12/21/2016] [Accepted: 01/03/2017] [Indexed: 12/20/2022]
Abstract
The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.
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Affiliation(s)
- D C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - N Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, MA, USA; Child and Adolescent Psychiatry, McLean Hospital, Belmont, MA, USA
| | - B G Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Occupational Therapy Program, Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - M B Prigge
- Department of Radiology, University of Utah, Salt Lake City, UT, USA; Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, UT, USA
| | - N Matsunami
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - K A Kellett
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - A Freeman
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - K L Kane
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - N Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - D P M Tromp
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - D J Destiche
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - D Samsin
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - B A Zielinski
- Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, UT, USA; Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - P T Fletcher
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; School of Computing, University of Utah, Salt Lake City, UT, USA
| | - J S Anderson
- Department of Radiology, University of Utah, Salt Lake City, UT, USA; Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
| | - A L Froehlich
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | - M F Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - E D Bigler
- Department of Psychology, Brigham Young University, Provo, UT, USA; Neuroscience Center, Brigham Young University, Provo, UT 84602, USA
| | - J E Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - A L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA; Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
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28
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Lehnhardt FG, Falter CM, Gawronski A, Pfeiffer K, Tepest R, Franklin J, Vogeley K. Sex-Related Cognitive Profile in Autism Spectrum Disorders Diagnosed Late in Life: Implications for the Female Autistic Phenotype. J Autism Dev Disord 2016; 46:139-154. [PMID: 26319250 DOI: 10.1007/s10803-015-2558-7] [Citation(s) in RCA: 84] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Females with high-functioning ASD are known to camouflage their autistic symptoms better than their male counterparts, making them prone to being under-ascertained and delayed in diagnostic assessment. Thus far the underlying cognitive processes that enable such successful socio-communicative adaptation are not well understood. The current results show sex-related differences in the cognitive profile of ASD individuals, which were diagnosed late in life exclusively. Higher verbal abilities were found in males (n = 69) as opposed to higher processing speed and better executive functions in females with ASD (n = 38). Since both sexes remained unidentified during childhood and adolescence, these results are suggestive for sex-distinctive cognitive strategies as an alternative to typically-developed reciprocal social behavior and social mimicry in high functioning ASD.
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Affiliation(s)
- Fritz-Georg Lehnhardt
- Department of Psychiatry and Psychotherapy, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
| | - Christine Michaela Falter
- Department of Psychiatry and Psychotherapy, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Astrid Gawronski
- Department of Psychiatry and Psychotherapy, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Kathleen Pfeiffer
- Department of Psychiatry and Psychotherapy, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Ralf Tepest
- Department of Psychiatry and Psychotherapy, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Jeremy Franklin
- Institute of Medical Statistics, Computer Science and Epidemiology (IMSIE), University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Kai Vogeley
- Department of Psychiatry and Psychotherapy, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.,Institute of Neuroscience and Medicine - Cognitive Neurosciences (INM-3), Research Center Juelich, 52425, Juelich, Germany
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29
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Dean DC, Travers BG, Adluru N, Tromp DP, Destiche DJ, Samsin D, Prigge MB, Zielinski BA, Fletcher PT, Anderson JS, Froehlich AL, Bigler ED, Lange N, Lainhart JE, Alexander AL. Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder. Brain Connect 2016; 6:415-33. [PMID: 27021440 PMCID: PMC4913512 DOI: 10.1089/brain.2015.0385] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
White matter microstructure forms a complex and dynamical system that is critical for efficient and synchronized brain function. Neuroimaging findings in children with autism spectrum disorder (ASD) suggest this condition is associated with altered white matter microstructure, which may lead to atypical macroscale brain connectivity. In this study, we used diffusion tensor imaging measures to examine the extent that white matter tracts are interrelated within ASD and typical development. We assessed the strength of inter-regional white matter correlations between typically developing and ASD diagnosed individuals. Using hierarchical clustering analysis, clustering patterns of the pairwise white matter correlations were constructed and revealed to be different between the two groups. Additionally, we explored the use of graph theory analysis to examine the characteristics of the patterns formed by inter-regional white matter correlations and compared these properties between ASD and typical development. We demonstrate that the ASD sample has significantly less coherence in white matter microstructure across the brain compared to that in the typical development sample. The ASD group also presented altered topological characteristics, which may implicate less efficient brain networking in ASD. These findings highlight the potential of graph theory based network characteristics to describe the underlying networks as measured by diffusion magnetic resonance imaging and furthermore indicates that ASD may be associated with altered brain network characteristics. Our findings are consistent with those of a growing number of studies and hypotheses that have suggested disrupted brain connectivity in ASD.
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Affiliation(s)
- Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
- Occupational Therapy Program, Department of Kinesiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Do P.M. Tromp
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | | | - Danica Samsin
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Molly B. Prigge
- Department of Radiology, University of Utah, Salt Lake City, Utah
- Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, Utah
| | - Brandon A. Zielinski
- Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, Utah
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - P. Thomas Fletcher
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah
- School of Computing, University of Utah, Salt Lake City, Utah
| | - Jeffrey S. Anderson
- Department of Radiology, University of Utah, Salt Lake City, Utah
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, Utah
| | | | - Erin D. Bigler
- Department of Psychology, Brigham Young University, Provo, Utah
- Neuroscience Center, Brigham Young University, Provo, Utah
| | - Nicholas Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, Massachusetts
- Neurostatistics Laboratory, McLean Hospital, Belmont, Massachusetts
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
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30
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Dean DC, O'Muircheartaigh J, Dirks H, Travers BG, Adluru N, Alexander AL, Deoni SCL. Mapping an index of the myelin g-ratio in infants using magnetic resonance imaging. Neuroimage 2016; 132:225-237. [PMID: 26908314 PMCID: PMC4851913 DOI: 10.1016/j.neuroimage.2016.02.040] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Revised: 02/07/2016] [Accepted: 02/12/2016] [Indexed: 12/03/2022] Open
Abstract
Optimal myelination of neuronal axons is essential for effective brain and cognitive function. The ratio of the axon diameter to the outer fiber diameter, known as the g-ratio, is a reliable measure to assess axonal myelination and is an important index reflecting the efficiency and maximal conduction velocity of white matter pathways. Although advanced neuroimaging techniques including multicomponent relaxometry (MCR) and diffusion tensor imaging afford insight into the microstructural characteristics of brain tissue, by themselves they do not allow direct analysis of the myelin g-ratio. Here, we show that by combining myelin content information (obtained with mcDESPOT MCR) with neurite density information (obtained through NODDI diffusion imaging) an index of the myelin g-ratio may be estimated. Using this framework, we present the first quantitative study of myelin g-ratio index changes across childhood, examining 18 typically developing children 3months to 7.5years of age. We report a spatio-temporal pattern of maturation that is consistent with histological and developmental MRI studies, as well as theoretical studies of the myelin g-ratio. This work represents the first ever in vivo visualization of the evolution of white matter g-ratio indices throughout early childhood.
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Affiliation(s)
- Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA.
| | | | - Holly Dirks
- Advanced Baby Imaging Lab, Brown University School of Engineering, Providence, RI 02912, USA
| | - Brittany G Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Kinesiology, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719, USA; Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Sean C L Deoni
- Advanced Baby Imaging Lab, Brown University School of Engineering, Providence, RI 02912, USA; Department of Pediatric Radiology, Children's Hospital Colorado, Aurora, CO, USA; Department of Radiology, University of Colorado Denver, Denver, CO, USA
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31
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Rommelse N, Langerak I, van der Meer J, de Bruijn Y, Staal W, Oerlemans A, Buitelaar J. Intelligence May Moderate the Cognitive Profile of Patients with ASD. PLoS One 2015; 10:e0138698. [PMID: 26444877 PMCID: PMC4596821 DOI: 10.1371/journal.pone.0138698] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 09/02/2015] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND The intelligence of individuals with Autism Spectrum Disorder (ASD) varies considerably. The pattern of cognitive deficits associated with ASD may differ depending on intelligence. We aimed to study the absolute and relative severity of cognitive deficits in participants with ASD in relation to IQ. METHODS A total of 274 children (M age = 12.1, 68.6% boys) participated: 30 ASD and 22 controls in the below average Intelligence Quotient (IQ) group (IQ<85), 57 ASD and 54 controls in the average IQ group (85<IQ<115) and 41 ASD and 70 controls in the above average IQ group (IQ>115). Matching for age, sex, Full Scale IQ (FSIQ), Verbal IQ (VIQ), Performance IQ (PIQ) and VIQ-PIQ difference was performed. Speed and accuracy of social cognition, executive functioning, visual pattern recognition and basic processing speed were examined per domain and as a composite score. RESULTS The composite score revealed a trend significant IQ by ASD interaction (significant when excluding the average IQ group). In absolute terms, participants with below average IQs performed poorest (regardless of diagnosis). However, in relative terms, above average intelligent participants with ASD showed the most substantial cognitive problems (particularly for social cognition, visual pattern recognition and verbal working memory) since this group differed significantly from the IQ-matched control group (p < .001), whereas this was not the case for below-average intelligence participants with ASD (p = .57). CONCLUSIONS In relative terms, cognitive deficits appear somewhat more severe in individuals with ASD and above average IQs compared to the below average IQ patients with ASD. Even though high IQ ASD individuals enjoy a certain protection from their higher IQ, they clearly demonstrate cognitive impairments that may be targeted in clinical assessment and treatment. Conversely, even though in absolute terms ASD patients with below average IQs were clearly more impaired than ASD patients with average to above average IQs, the differences in cognitive functioning between participants with and without ASD on the lower end of the IQ spectrum were less pronounced. Clinically this may imply that cognitive assessment and training of cognitive skills in below average intelligent children with ASD may be a less fruitful endeavour. These findings tentatively suggest that intelligence may act as a moderator in the cognitive presentation of ASD, with qualitatively different cognitive processes affected in patients at the high and low end of the IQ spectrum.
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Affiliation(s)
- Nanda Rommelse
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, The Netherlands
- Karakter, Child and Adolescent Psychiatry University Centre Nijmegen, Nijmegen, the Netherlands
- * E-mail:
| | - Ilse Langerak
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, The Netherlands
| | - Jolanda van der Meer
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Cognitive Neuroscience, Nijmegen, The Netherlands
| | - Yvette de Bruijn
- Karakter, Child and Adolescent Psychiatry University Centre Nijmegen, Nijmegen, the Netherlands
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Cognitive Neuroscience, Nijmegen, The Netherlands
| | - Wouter Staal
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, The Netherlands
- Karakter, Child and Adolescent Psychiatry University Centre Nijmegen, Nijmegen, the Netherlands
| | - Anoek Oerlemans
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, The Netherlands
- Karakter, Child and Adolescent Psychiatry University Centre Nijmegen, Nijmegen, the Netherlands
| | - Jan Buitelaar
- Karakter, Child and Adolescent Psychiatry University Centre Nijmegen, Nijmegen, the Netherlands
- Radboud University Nijmegen Medical Centre, Nijmegen, Donders Institute for Brain, Cognition and Behavior, Department of Cognitive Neuroscience, Nijmegen, The Netherlands
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Green RR, Bigler ED, Froehlich A, Prigge MBD, Travers BG, Cariello AN, Anderson JS, Zielinski BA, Alexander A, Lange N, Lainhart JE. Beery VMI performance in autism spectrum disorder. Child Neuropsychol 2015; 22:795-817. [PMID: 26292997 DOI: 10.1080/09297049.2015.1056131] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Few studies have examined the visuomotor integration (VMI) abilities of individuals with autism spectrum disorder (ASD). An all-male sample consisting of 56 ASD participants (ages 3-23 years) and 36 typically developing (TD) participants (ages 4-26 years) completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI) as part of a larger neuropsychological battery. Participants were also administered standardized measures of intellectual functioning and the Social Responsiveness Scale (SRS), which assesses autism and autism-like traits. The ASD group performed significantly lower on the Beery VMI and on all IQ measures compared to the TD group. VMI performance was significantly correlated with full scale IQ (FSIQ), performance IQ (PIQ), and verbal IQ (VIQ) in the TD group only. However, when FSIQ was taken into account, no significant Beery VMI differences between groups were observed. Only one TD participant scored 1.5 standard deviations (SDs) below the Beery VMI normative sample mean, in comparison to 21% of the ASD sample. As expected, the ASD group was rated as having significantly higher levels of social impairment on the SRS compared to the TD group across all major domains. However, level of functioning on the SRS was not associated with Berry VMI performance. These findings demonstrate that a substantial number of individuals with ASD experience difficulties compared to TD in performing VMI-related tasks, and that VMI is likely affected by general cognitive ability. The fact that lowered Beery VMI performance occurred only within a subset of individuals with ASD and did not correlate with SRS would indicate that visuomotor deficits are not a core feature of ASD, even though they present at a higher rate of impairment than observed in TD participants.
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Affiliation(s)
- Ryan R Green
- a Department of Psychology , Brigham Young University , Provo , UT , USA
| | - Erin D Bigler
- a Department of Psychology , Brigham Young University , Provo , UT , USA.,b Neuroscience Center , Brigham Young University , Provo , UT , USA.,c Department of Psychiatry , University of Utah , Salt Lake City , UT , USA
| | - Alyson Froehlich
- c Department of Psychiatry , University of Utah , Salt Lake City , UT , USA
| | - Molly B D Prigge
- c Department of Psychiatry , University of Utah , Salt Lake City , UT , USA
| | - Brittany G Travers
- d Waisman Laboratory for Brain Imaging and Behavior , University of Wisconsin , Madison , WI , USA
| | - Annahir N Cariello
- c Department of Psychiatry , University of Utah , Salt Lake City , UT , USA
| | - Jeffrey S Anderson
- e Department of Radiology , University of Utah , Salt Lake City , UT , USA
| | - Brandon A Zielinski
- f Department of Pediatrics and Neurology, School of Medicine , University of Utah , Salt Lake City , UT , USA
| | - Andrew Alexander
- d Waisman Laboratory for Brain Imaging and Behavior , University of Wisconsin , Madison , WI , USA.,g Department of Medical Physics , University of Wisconsin , Madison , WI , USA.,h Department of Psychiatry , University of Wisconsin , Madison , WI , USA
| | - Nicholas Lange
- i Departments of Psychiatry and Biostatistics , Harvard University , Boston , MA , USA.,j Neurostatistics Laboratory , McLean Hospital , Belmont , MA , USA
| | - Janet E Lainhart
- d Waisman Laboratory for Brain Imaging and Behavior , University of Wisconsin , Madison , WI , USA.,h Department of Psychiatry , University of Wisconsin , Madison , WI , USA
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Jantz PB, Bigler ED, Froehlich AL, Prigge MBD, Cariello AN, Travers BG, Anderson J, Zielinski BA, Alexander AL, Lange N, Lainhart JE. WIDE RANGE ACHIEVEMENT TEST IN AUTISM SPECTRUM DISORDER: TEST-RETEST STABILITY. Psychol Rep 2015; 116:674-84. [PMID: 25871566 DOI: 10.2466/03.15.pr0.116k24w8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The principal goal of this descriptive study was to establish the test-retest stability of the Reading, Spelling, and Arithmetic subtest scores of the Wide Range Achievement Test (WRAT-3) across two administrations in individuals with autism spectrum disorder. Participants (N = 31) were males ages 6-22 years (M = 15.2, SD = 4.0) who were part of a larger ongoing longitudinal study of brain development in children and adults with autism spectrum disorder (N = 185). Test-retest stability for all three subtests remained consistent across administration periods (M = 31.8 mo., SD = 4.1). Age at time of administration, time between administrations, and test form did not significantly influence test-retest stability. Results indicated that for research involving individuals with autism spectrum disorder with a full scale intelligence quotient above 75, the WRAT-3 Spelling and Arithmetic subtests have acceptable test-retest stability over time and the Reading subtest has moderate test-retest stability over time.
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Affiliation(s)
| | - Erin D Bigler
- 2 Department of Psychology, Brigham Young University
| | | | - Molly B D Prigge
- 4 Department of Pediatrics, School of Medicine, University of Utah, Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison
| | | | - Brittany G Travers
- 6 Occupational Therapy Program, Department of Kinesiology, Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison
| | - Jeffrey Anderson
- 7 Departments of Radiology and Bioengineering, University of Utah
| | - Brandon A Zielinski
- 8 Department of Pediatrics and Neurology, School of Medicine, University of Utah
| | - Andrew L Alexander
- 9 Department of Medical Physics, Department of Psychiatry, Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison
| | - Nicholas Lange
- 10 Departments of Psychiatry and Biostatistics, Harvard University, Neurostatistics Laboratory, McLean Hospital, Belmont, MA
| | - Janet E Lainhart
- 11 Department of Psychiatry, Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison
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High resolution magnetic resonance imaging for characterization of the neuroligin-3 knock-in mouse model associated with autism spectrum disorder. PLoS One 2014; 9:e109872. [PMID: 25299583 PMCID: PMC4192590 DOI: 10.1371/journal.pone.0109872] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Accepted: 09/14/2014] [Indexed: 11/19/2022] Open
Abstract
Autism spectrum disorders (ASD) comprise an etiologically heterogeneous set of neurodevelopmental disorders. Neuroligin-3 (NL-3) is a cell adhesion protein that mediates synapse development and has been implicated in ASD. We performed ex-vivo high resolution magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and behavioral (social approach and zero maze) tests at 3 different time points (30, 50 and 70 days-of-age) on NL-3 and wild-type littermates to assess developmental brain abnormalities in NL-3 mice. MRI data were segmented in 39 different gray and white matter regions. Volumetric measurements, along with DTI indices from these segmented regions were also performed. After controlling for age and gender, the NL-3 knock-in animals demonstrated significantly reduced sociability and lower anxiety-related behavior in comparison to their wild type littermates. Significantly reduced volume of several white and gray matter regions in the NL-3 knock-in mice were also observed after considering age, gender and time point as covariates. These findings suggest that structural changes in the brain of NL-3 mice are induced by the mutation in the NL-3 gene. No significant differences in DTI indices were observed, which suggests that the NL-3 mutation may not have a profound effect on water diffusion as detected by DTI. The volumetric and DTI studies aid in understanding the biology of disrupting function on an ASD risk model and may assist in the development of imaging biomarkers for ASD.
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Collier Q, Veraart J, Jeurissen B, den Dekker AJ, Sijbers J. Iterative reweighted linear least squares for accurate, fast, and robust estimation of diffusion magnetic resonance parameters. Magn Reson Med 2014; 73:2174-84. [PMID: 24986440 DOI: 10.1002/mrm.25351] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2014] [Revised: 05/20/2014] [Accepted: 06/13/2014] [Indexed: 12/20/2022]
Abstract
PURPOSE Diffusion-weighted magnetic resonance imaging suffers from physiological noise, such as artifacts caused by motion or system instabilities. Therefore, there is a need for robust diffusion parameter estimation techniques. In the past, several techniques have been proposed, including RESTORE and iRESTORE (Chang et al. Magn Reson Med 2005; 53:1088-1095; Chang et al. Magn Reson Med 2012; 68:1654-1663). However, these techniques are based on nonlinear estimators and are consequently computationally intensive. METHOD In this work, we present a new, robust, iteratively reweighted linear least squares (IRLLS) estimator. IRLLS performs a voxel-wise identification of outliers in diffusion-weighted magnetic resonance images, where it exploits the natural skewness of the data distribution to become more sensitive to both signal hyperintensities and signal dropouts. RESULTS Both simulations and real data experiments were conducted to compare IRLLS with other state-of-the-art techniques. While IRLLS showed no significant loss in accuracy or precision, it proved to be substantially faster than both RESTORE and iRESTORE. In addition, IRLLS proved to be even more robust when considering the overestimation of the noise level or when the signal-to-noise ratio is low. CONCLUSION The substantially shortened calculation time in combination with the increased robustness and accuracy, make IRLLS a practical and reliable alternative to current state-of-the-art techniques for the robust estimation of diffusion-weighted magnetic resonance parameters.
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Affiliation(s)
- Quinten Collier
- iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Jelle Veraart
- iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Ben Jeurissen
- iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Arnold J den Dekker
- iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium.,Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
| | - Jan Sijbers
- iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium
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