. 2014 Jun;19(6):659-67.

doi: 10.1038/mp.2013.78. Epub 2013 Jun 18.

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

A Di Martino¹, C-G Yan², Q Li³, E Denio¹, F X Castellanos⁴, K Alaerts⁵, J S Anderson⁶, M Assaf⁷, S Y Bookheimer⁸, M Dapretto⁹, B Deen¹⁰, S Delmonte¹¹, I Dinstein¹², B Ertl-Wagner¹³, D A Fair¹⁴, L Gallagher¹¹, D P Kennedy¹⁵, C L Keown¹⁶, C Keysers¹⁷, J E Lainhart¹⁸, C Lord¹⁹, B Luna²⁰, V Menon²¹, N J Minshew²², C S Monk²³, S Mueller¹³, R-A Müller¹⁶, M B Nebel²⁴, J T Nigg²⁵, K O'Hearn²⁰, K A Pelphrey²⁶, S J Peltier²³, J D Rudie²⁷, S Sunaert²⁸, M Thioux¹⁷, J M Tyszka²⁹, L Q Uddin²¹, J S Verhoeven²⁸, N Wenderoth³⁰, J L Wiggins²³, S H Mostofsky³¹, M P Milham³²

Affiliations

¹ Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the NYU Child Study Center, New York University Langone Medical Center, New York, NY, USA.
² Nathan S Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
³ Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
⁴ 1] Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the NYU Child Study Center, New York University Langone Medical Center, New York, NY, USA [2] Nathan S Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
⁵ 1] Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the NYU Child Study Center, New York University Langone Medical Center, New York, NY, USA [2] KU Leuven, Leuven, Belgium.
⁶ 1] Division of Neuroradiology, University of Utah, Salt Lake City, UT, USA [2] Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA [3] The Brain Institute at the University of Utah, Salt Lake City, UT, USA [4] Department of Bioengineering, University of Utah, Salt Lake City, UT, USA.
⁷ 1] Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA [2] Yale School of Medicine, New Haven, CT, USA.
⁸ 1] Center for Cognitive Neuroscience, UCLA, Los Angeles, CA, USA [2] Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA [3] Interdepartmental Neuroscience Program, UCLA, Los Angeles, CA, USA [4] David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
⁹ 1] Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA [2] Interdepartmental Neuroscience Program, UCLA, Los Angeles, CA, USA [3] Ahmanson-Lovelace Brain Mapping Center, UCLA, Los Angeles, CA, USA.
¹⁰ 1] Yale School of Medicine, New Haven, CT, USA [2] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
¹¹ Department of Psychiatry and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, UK.
¹² 1] Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, USA [2] Psychology, Ben Gurion University of the Negev, Beersheba, Israel.
¹³ Institute for Clinical Radiology, Ludwig Maximilians University Munich, Munich, Germany.
¹⁴ Behavioral Neuroscience and Psychiatry Departments, and Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, USA.
¹⁵ 1] Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA [2] Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
¹⁶ Department of Psychology, San Diego State University, San Diego, CA, USA.
¹⁷ 1] Netherlands Institute for Neuroscience, Royal Dutch Academy of Science (KNAW), Amsterdam, The Netherlands [2] BCN NeuroImaging Center, University Medical Center Groningen, Rijksuniversiteit Groningen, Groningen, The Netherlands.
¹⁸ 1] Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, WI, USA [2] Department of Psychiatry, Division of Child and Adolescent Psychiatry, University of Wisconsin, Madison, WI, USA.
¹⁹ Weill-Cornell Medical College, New York, NY, USA.
²⁰ University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
²¹ Stanford University, Stanford, CA, USA.
²² Departments of Psychiatry and Neurology, University of Pittsburgh, Pittsburgh, PA, USA.
²³ University of Michigan, Ann Arbor, MI, USA.
²⁴ Laboratory for Neurocognitive and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA.
²⁵ Oregon Health and Science University, Portland, OR, USA.
²⁶ Yale School of Medicine, New Haven, CT, USA.
²⁷ 1] Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA [2] Interdepartmental Neuroscience Program, UCLA, Los Angeles, CA, USA [3] David Geffen School of Medicine, UCLA, Los Angeles, CA, USA [4] Ahmanson-Lovelace Brain Mapping Center, UCLA, Los Angeles, CA, USA.
²⁸ Translational MRI, University of Leuven (KU Leuven), Leuven, Belgium.
²⁹ Division of Biology, Caltech, Pasadena, CA, USA.
³⁰ KU Leuven, Leuven, Belgium.
³¹ 1] Laboratory for Neurocognitive and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA [2] Departments of Neurology and Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA.
³² 1] Nathan S Kline Institute for Psychiatric Research, Orangeburg, NY, USA [2] Center for the Developing Brain, Child Mind Institute, New York, NY, USA.

PMID: 23774715
PMCID: PMC4162310
DOI: 10.1038/mp.2013.78

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

A Di Martino et al. Mol Psychiatry. 2014 Jun.

. 2014 Jun;19(6):659-67.

doi: 10.1038/mp.2013.78. Epub 2013 Jun 18.

Authors

Affiliations

¹ Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the NYU Child Study Center, New York University Langone Medical Center, New York, NY, USA.
² Nathan S Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
³ Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
⁴ 1] Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the NYU Child Study Center, New York University Langone Medical Center, New York, NY, USA [2] Nathan S Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
⁵ 1] Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the NYU Child Study Center, New York University Langone Medical Center, New York, NY, USA [2] KU Leuven, Leuven, Belgium.
⁶ 1] Division of Neuroradiology, University of Utah, Salt Lake City, UT, USA [2] Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA [3] The Brain Institute at the University of Utah, Salt Lake City, UT, USA [4] Department of Bioengineering, University of Utah, Salt Lake City, UT, USA.
⁷ 1] Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA [2] Yale School of Medicine, New Haven, CT, USA.
⁸ 1] Center for Cognitive Neuroscience, UCLA, Los Angeles, CA, USA [2] Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA [3] Interdepartmental Neuroscience Program, UCLA, Los Angeles, CA, USA [4] David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
⁹ 1] Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA [2] Interdepartmental Neuroscience Program, UCLA, Los Angeles, CA, USA [3] Ahmanson-Lovelace Brain Mapping Center, UCLA, Los Angeles, CA, USA.
¹⁰ 1] Yale School of Medicine, New Haven, CT, USA [2] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
¹¹ Department of Psychiatry and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, UK.
¹² 1] Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, USA [2] Psychology, Ben Gurion University of the Negev, Beersheba, Israel.
¹³ Institute for Clinical Radiology, Ludwig Maximilians University Munich, Munich, Germany.
¹⁴ Behavioral Neuroscience and Psychiatry Departments, and Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, USA.
¹⁵ 1] Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA [2] Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
¹⁶ Department of Psychology, San Diego State University, San Diego, CA, USA.
¹⁷ 1] Netherlands Institute for Neuroscience, Royal Dutch Academy of Science (KNAW), Amsterdam, The Netherlands [2] BCN NeuroImaging Center, University Medical Center Groningen, Rijksuniversiteit Groningen, Groningen, The Netherlands.
¹⁸ 1] Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, WI, USA [2] Department of Psychiatry, Division of Child and Adolescent Psychiatry, University of Wisconsin, Madison, WI, USA.
¹⁹ Weill-Cornell Medical College, New York, NY, USA.
²⁰ University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
²¹ Stanford University, Stanford, CA, USA.
²² Departments of Psychiatry and Neurology, University of Pittsburgh, Pittsburgh, PA, USA.
²³ University of Michigan, Ann Arbor, MI, USA.
²⁴ Laboratory for Neurocognitive and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA.
²⁵ Oregon Health and Science University, Portland, OR, USA.
²⁶ Yale School of Medicine, New Haven, CT, USA.
²⁷ 1] Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA [2] Interdepartmental Neuroscience Program, UCLA, Los Angeles, CA, USA [3] David Geffen School of Medicine, UCLA, Los Angeles, CA, USA [4] Ahmanson-Lovelace Brain Mapping Center, UCLA, Los Angeles, CA, USA.
²⁸ Translational MRI, University of Leuven (KU Leuven), Leuven, Belgium.
²⁹ Division of Biology, Caltech, Pasadena, CA, USA.
³⁰ KU Leuven, Leuven, Belgium.
³¹ 1] Laboratory for Neurocognitive and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA [2] Departments of Neurology and Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA.
³² 1] Nathan S Kline Institute for Psychiatric Research, Orangeburg, NY, USA [2] Center for the Developing Brain, Child Mind Institute, New York, NY, USA.

PMID: 23774715
PMCID: PMC4162310
DOI: 10.1038/mp.2013.78

Abstract

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest

Catherine Lord receives royalties from the publication of the Autism Diagnostic Interview–Revised and the Autism Diagnostic Observation Schedule. All other authors declare no conflict of interest.

Figures

**Figure 1. ABIDE Sample Characteristics**
**(A)** Total number of participants per group (green=Typical Controls [TC], purple=Autism Spectrum Disorders [ASD]) for each contributing site ordered as a function of sample size (labeled alphabetically, see Supplementary Table 2 for label key). The same site labels are used for Figures 1 B-F. (B) Number of males (blue-white) and females (red) for each site irrespective of diagnostic group (groups were matched for sex). (C) Age (in years) for all individuals per site (ordered by youngest age included per site) irrespective of diagnostic group (groups were age matched). Each site’s mean is represented as a solid red line; the median age across sites (14.7 years) is depicted with a thick red dashed line; 25^th, 75^th, and 90^th percentiles (11.7, 20.1, and 28.3 years, respectively) are represented by thin red dashed lines. **(D)** Distribution of full IQ (FIQ) standard scores per site (ordered by lowest FIQ included per site) for individuals with ASD (purple, left plot) and TC (green, right plot), respectively. Solid black lines indicate mean FIQ per site. **(E)** The Tukey box-whiskers plots depict the distribution of Total Autism Diagnostic Observation Scale (ADOS) scores (i.e., sum of scaled Communication and Reciprocal Social interaction subtotals) for individuals with ASD in the 13 sites using the ADOS. **(F)** Number of probands assigned to specific ASD diagnostic categories per site. Categories were DSM-IV-TR Autistic Disorder (red), Asperger Syndrome (aqua green), and Pervasive Developmental Disorder—Not Otherwise Specified (PDD-NOS) (white-gray pattern), and individuals identified as ASD but not further differentiated into specific DSM-IV-TR subtypes (gray). Data displayed in D and E were imputed as described in main text.

**Figure 2. Whole-Brain Intrinsic Functional Connectivity (iFC) Analyses**
**(A)** Significant group differences (i.e., Autism Spectrum Disorders [ASD] vs. Typical Controls [TC]) for iFC between each of the 112 parcellation units (56 per hemisphere) included in the structural Harvard-Oxford Atlas (HOA). Parcellations are represented with their center of mass overlaid as spheres on glass brains. The upper panel shows the intrinsic functional connections (blue lines) that were significantly weaker in ASD vs. TC. The lower panel shows the intrinsic functional connections that were significantly stronger in ASD relative to TC (red lines). Each HOA unit is colored based on its membership in the six functional divisions per Mesulam et al. [yellow=primary sensorimotor (SM); green=unimodal association; blue=heteromodal association; orange=paralimbic; red=limbic; pink=subcortical]. Interhemispheric iFC is noted on dorsal and coronal views. Glass brains (left lateral, dorsal, and coronal views, shown from left to right) are generated using BrainNet Viewer (http://www.nitrc.org/projects/bnv/). Displayed results are corrected for multiple comparisons using false discovery rate (FDR) at p<0.05. **(B)** The table summarizes the absolute number and percentage of node-to-node iFC surviving statistical threshold for group comparisons within and between functional divisions. Gray cells represent absence of significant iFC, blue cells represent ASD-related hypoconnectivity (*Hypo*: ASD<TC), while red cells represent hyperconnectivity (*Hyper*: ASD>TC). Blue and red shadings decrease proportionally from the highest percentage (37%) to the lowest (~0%). See Supplementary Tables 4, 5 and 6 for results based on lobar and hemispheric divisions as well as for those based on the Crad-200 functional parcellation and Supplementary Information for further discussion on the approach.

**Figure 3. Regional Measures of Intrinsic Functional Architecture**
**(A)** Z maps of the grand means (i.e., across all 763 individuals) and **(B)** significant group differences between individuals with Autism Spectrum Disorders (ASD) and Typical Controls (TC) for each of the four regional measures examined. These were fractional amplitude of low frequency fluctuations (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), and degree centrality (DC). We employed Gaussian random field theory to carry out cluster-level corrections for multiple comparisons (voxel-level Z>2.3; cluster significance: p<0.05, corrected). Significant clusters are overlaid on inflated surface maps generated using BrainNet Viewer (http://www.nitrc.org/projects/bnv/), as well as on axial images generated with REST Slice Viewer (http://www.restfmri.net). L= Left hemisphere; R= Right hemisphere.

**Figure 4. Overlap Between Regional Measures of Intrinsic Brain Function**
**(A)** Surface and axial maps depict the extent of overlap for significant group differences (i.e., Autism Spectrum Disorders [ASD] vs. Typical Controls [TC]) among any of the four regional measures of intrinsic brain function shown in Figure 3. Purple clusters represent areas of significant group differences emerging for only one measure; orange and yellow clusters indicate measures with overlap among 2 and 3 measures, respectively. **(B)** For each of the yellow and orange clusters in panel A, the table lists the cluster’s anatomical area label, cluster size in number of voxels, and stereotaxic coordinates for the center of mass in Montreal Neurological Institute (MNI) coordinates, the specific measures involved in the overlap, and the group difference direction (ASD>TC in red, ASD<TC in blue). L= Left hemisphere; R= Right hemisphere.

**Figure 5. Seed Based Correlation Analyses: Default Network**
**(A)** Z maps of the grand means (i.e., across all 763 individuals) and **(B)** of the group differences between individuals with Autism Spectrum Disorders (ASD) and Typical Controls (TC) for the two midline core seed regions located in Posterior Cingulate Cortex (PCC) and Anterior Medial Prefrontal Cortex (aMPFC). Seeds were centered at Montreal Neurological Institute stereotaxic coordinates x=−8, y=−56, z=26 for PCC and x=−6, y=52, z=−2 for aMPFC, and are depicted as white dots on the surface maps. Gaussian random field theory was used to carry out cluster-level corrections for multiple comparisons (voxel-level Z>2.3; cluster significance: p<0.05, corrected). Significant clusters are overlaid on inflated surface maps generated using BrainNet Viewer (http://www.nitrc.org/projects/bnv/), as well as on axial images generated with REST Slice Viewer (http://www.restfmri.net). L= Left hemisphere; R= Right hemisphere.

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The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

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The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

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