Literature DB >> 18775497

The myth of the normal, average human brain--the ICBM experience: (1) subject screening and eligibility.

John C Mazziotta1, Roger Woods, Marco Iacoboni, Nancy Sicotte, Kami Yaden, Mary Tran, Courtney Bean, Jonas Kaplan, Arthur W Toga.   

Abstract

In the course of developing an atlas and reference system for the normal human brain throughout the human age span from structural and functional brain imaging data, the International Consortium for Brain Mapping (ICBM) developed a set of "normal" criteria for subject inclusion and the associated exclusion criteria. The approach was to minimize inclusion of subjects with any medical disorders that could affect brain structure or function. In the past two years, a group of 1685 potential subjects responded to solicitation advertisements at one of the consortium sites (UCLA). Subjects were screened by a detailed telephone interview and then had an in-person history and physical examination. Of those who responded to the advertisement and considered themselves to be normal, only 31.6% (532 subjects) passed the telephone screening process. Of the 348 individuals who submitted to in-person history and physical examinations, only 51.7% passed these screening procedures. Thus, only 10.7% of those individuals who responded to the original advertisement qualified for imaging. The most frequent cause for exclusion in the second phase of subject screening was high blood pressure followed by abnormal signs on neurological examination. It is concluded that the majority of individuals who consider themselves normal by self-report are found not to be so by detailed historical interviews about underlying medical conditions and by thorough medical and neurological examinations. Recommendations are made with regard to the inclusion of subjects in brain imaging studies and the criteria used to select them.

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Mesh:

Year:  2008        PMID: 18775497      PMCID: PMC2651672          DOI: 10.1016/j.neuroimage.2008.07.062

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  25 in total

1.  The structural brain correlates of neurological soft signs in healthy individuals.

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2.  Defining the phenotype to discover the genotype.

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4.  Volunteers for biomedical research. Recruitment and screening of normal controls.

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5.  Exploiting a research underclass in phase 1 clinical trials.

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Journal:  N Engl J Med       Date:  2008-05-29       Impact factor: 91.245

6.  Incidence and risk factors of silent brain infarcts in the population-based Rotterdam Scan Study.

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Authors:  Sarah E Vermeer; Monika Hollander; Ewoud J van Dijk; Albert Hofman; Peter J Koudstaal; Monique M B Breteler
Journal:  Stroke       Date:  2003-04-10       Impact factor: 7.914

8.  Migraine as a risk factor for subclinical brain lesions.

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9.  Stroke risk profile predicts white matter hyperintensity volume: the Framingham Study.

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10.  Recommendations for blood pressure measurement in humans: an AHA scientific statement from the Council on High Blood Pressure Research Professional and Public Education Subcommittee.

Authors:  Thomas G Pickering; John E Hall; Lawrence J Appel; Bonita E Falkner; John W Graves; Martha N Hill; Daniel H Jones; Theodore Kurtz; Sheldon G Sheps; Edward J Roccella
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  23 in total

Review 1.  Do brain image databanks support understanding of normal ageing brain structure? A systematic review.

Authors:  David Alexander Dickie; Dominic E Job; Ian Poole; Trevor S Ahearn; Roger T Staff; Alison D Murray; Joanna M Wardlaw
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2.  Relationships between gray matter, body mass index, and waist circumference in healthy adults.

Authors:  Florian Kurth; Jennifer G Levitt; Owen R Phillips; Eileen Luders; Roger P Woods; John C Mazziotta; Arthur W Toga; Katherine L Narr
Journal:  Hum Brain Mapp       Date:  2012-03-15       Impact factor: 5.038

3.  Surpassing the Target: How a Recruitment Campaign Transformed the Participant Accrual Trajectory in the Epilepsy Phenome/Genome Project.

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Authors:  Eileen Luders; Paul M Thompson; Florian Kurth; Jui-Yang Hong; Owen R Phillips; Yalin Wang; Boris A Gutman; Yi-Yu Chou; Katherine L Narr; Arthur W Toga
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5.  Characteristics of canonical intrinsic connectivity networks across tasks and monozygotic twin pairs.

Authors:  Craig A Moodie; Krista M Wisner; Angus W MacDonald
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6.  Investigating the differential contributions of sex and brain size to gray matter asymmetry.

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7.  Safety, Science, or Both? Deceptive Healthy Volunteers: Psychiatric Conditions Uncovered by Objective Methods of Screening.

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Journal:  Psychosomatics       Date:  2017-05-09       Impact factor: 2.386

8.  Age but no sex effects on subareas of the amygdala.

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9.  Why sex matters: brain size independent differences in gray matter distributions between men and women.

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10.  Why size matters: differences in brain volume account for apparent sex differences in callosal anatomy: the sexual dimorphism of the corpus callosum.

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