Offering to Share: How to Put Heads Together in Autism Neuroimaging

Department of Human Development, Cornell University, Martha Van Rensselaer Hall, Ithaca, NY 14853-4401, USA.
Journal of Autism and Developmental Disorders (Impact Factor: 3.34). 02/2008; 38(1):2-13. DOI: 10.1007/s10803-006-0352-2
Source: PubMed


Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and recommendations for raw data, outlines a core protocol including multispectral structural and diffusion-tensor imaging and optional extensions, provides for the collection of prospective, confound-free normative data, and extends sharing and collaborative development not only to data but to the analytical tools and methods applied to these data. A theme in these requirements is the need to preserve creative approaches and risk-taking within individual laboratories at the same time as common standards are provided for these laboratories to build on.

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    • "In ASD on the other hand, there has been an international explosion of investigation at numerous institutions, across ages, IQ ranges, and diagnostic severity, which has resulted in at times seemingly contradictory results. A call for collaboration (150) has been met with a first international compilation of neuroimaging datasets, which has helped to clarify some discrepancies in the literature with respect to fMRI (146). Going forward, ongoing collaboration to facilitate large scale, prospective, longitudinal neuroimaging studies, will be necessary to separate signals from noise in these complex and heterogeneous diseases. "
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    ABSTRACT: Background: Autism spectrum disorder (ASD) and childhood onset schizophrenia (COS) are pediatric neurodevelopmental disorders associated with significant morbidity. Both conditions are thought to share an underlying genetic architecture. A comparison of neuroimaging findings across ASD and COS with a focus on altered neurodevelopmental trajectories can shed light on potential clinical biomarkers and may highlight an underlying etiopathogenesis. Methods: A comprehensive review of the medical literature was conducted to summarize neuroimaging data with respect to both conditions in terms of structural imaging (including volumetric analysis, cortical thickness and morphology, and region of interest studies), white matter analysis (include volumetric analysis and diffusion tensor imaging) and functional connectivity. Results: In ASD, a pattern of early brain overgrowth in the first few years of life is followed by dysmaturation in adolescence. Functional analyses have suggested impaired long-range connectivity as well as increased local and/or subcortical connectivity in this condition. In COS, deficits in cerebral volume, cortical thickness, and white matter maturation seem most pronounced in childhood and adolescence, and may level off in adulthood. Deficits in local connectivity, with increased long-range connectivity have been proposed, in keeping with exaggerated cortical thinning. Conclusion: The neuroimaging literature supports a neurodevelopmental origin of both ASD and COS and provides evidence for dynamic changes in both conditions that vary across space and time in the developing brain. Looking forward, imaging studies which capture the early post natal period, which are longitudinal and prospective, and which maximize the signal to noise ratio across heterogeneous conditions will be required to translate research findings into a clinical environment.
    Frontiers in Psychiatry 12/2013; 4:175. DOI:10.3389/fpsyt.2013.00175
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    • "Future studies of ASDs should ideally try to be performed on samples in which participants are matched across groups by IQ, age and gender, and recognizing the main comorbidities. A strategy that has recently been developed and that could help to minimize the issues related to the heterogeneity of the sample is the idea of "data sharing" proposed by Belmonte et al. [60]. Indeed, sharing data between different laboratories, although it needs to be carefully standardized, at least regarding the derived data, could contribute, by increasing the numerosity of subjects involved, and therefore of the data collected, the biases due to the heterogeneity of samples. "
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    ABSTRACT: Autistic Spectrum Disorders (ASDs) are a set of complex developmental disabilities defined by impairment in social interaction and communication, as well as by restricted interests or repetitive behaviors. Neuroimaging studies have substantially advanced our understanding of the neural mechanisms that underlie the core symptoms of ASDs. Nevertheless, a number of challenges still remain in the application of neuroimaging techniques to the study of ASDs. We review three major conceptual and methodological challenges that complicate the interpretation of findings from neuroimaging studies in ASDs, and that future imaging studies should address through improved designs. These include: (1) identification and implementation of tasks that more specifically target the neural processes of interest, while avoiding the confusion that the symptoms of ASD may impose on both the performance of the task and the detection of brain activations; (2) the inconsistency that disease heterogeneity in persons with ASD can generate on research findings, particularly heterogeneity of symptoms, symptom severity, differences in IQ, total brain volume, and psychiatric comorbidity; and (3) the problems with interpretation of findings from cross-sectional studies of persons with ASD across differing age groups. Failure to address these challenges will continue to hinder our ability to distinguish findings that outline the causes of ASDs from brain processes that represent downstream or compensatory responses to the presence of the disease. Here we propose strategies to address these issues: 1) the use of simple and elementary tasks, that are easier to understand for autistic subjects; 2) the scanning of a more homogenous group of persons with ASDs, preferably at younger age; 3) the performance of longitudinal studies, that may provide more straight forward and reliable results. We believe that this would allow for a better understanding of both the central pathogenic processes and the compensatory responses in the brain of persons suffering from ASDs.
    Behavioral and Brain Functions 03/2010; 6(1):17. DOI:10.1186/1744-9081-6-17 · 1.97 Impact Factor
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    • "Hence, data sharing in imaging informatics is a fundamental issue. However, image data sharing has scientific, technical and social obstacles (Belmonte et al., 2008). For example, human imaging data sharing should meet the need for protection of patient privacy, and compliance with applicable regulations and guidelines including those of the Institutional Review Board, Health Insurance Portability and Accountability Act (HIPAA), and other institutional, local, state and federal government and community bodies. "
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    ABSTRACT: Imaging informatics has emerged as a major research theme in biomedicine in the last few decades. Currently, personalised, predictive and preventive patient care is believed to be one of the top priorities in biomedical research and practice. Imaging informatics plays a major role in biomedicine studies. This paper reviews main applications and challenges of imaging informatics in biomedicine.
    International Journal of Functional Informatics and Personalised Medicine 01/2009; 2(2):125-135. DOI:10.1504/IJFIPM.2009.027587
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