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

Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA.
NeuroImage (Impact Factor: 6.13). 09/2008; 44(3):914-22. DOI: 10.1016/j.neuroimage.2008.07.062
Source: PubMed

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.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Intrinsic connectivity networks (ICNs) are becoming more prominent in the analyses of in vivo brain activity as the field of neurometrics has revealed their importance for augmenting traditional cognitive neuroscience approaches. Consequently, tools that assess the coherence, or connectivity, and morphology of ICNs are being developed to support inferences and assumptions about the dynamics of the brain. Recently, we reported trait-like profiles of ICNs showing reliability over time and reproducibility across different contexts. This study further examined the trait-like and familial nature of ICNs by utilizing two divergent task paradigms in twins. The study aimed to identify stable network phenotypes that exhibited sensitivity to individual differences and external perturbations in task demands. Analogous ICNs were detected in each task and these ICNs showed consistency in morphology and intranetwork coherence across tasks, whereas the ICN timecourse dynamics showed sensitivity to task demands. Specifically, the timecourse of an arm/hand sensorimotor network showed the strongest correlation with the timeline of a hand imitation task, and the timecourse of a language-processing network showed the strongest temporal association with a verb generation task. The area V1/simple visual stimuli network exhibited the most consistency in morphology, coherence, and timecourse dynamics within and across tasks. Similarly, this network exhibited familiality in all three domains as well. Hence, this experiment is a proof of principle that the morphology and coherence of ICNs can be consistent both within and across tasks, that ICN timecourses can be differentially and meaningfully modulated by a task, and that these domains can exhibit familiality. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
    Human Brain Mapping 07/2014; · 6.92 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Numerous studies have demonstrated a sexual dimorphism of the human corpus callosum. However, the question remains if sex differences in brain size, which typically is larger in men than in women, or biological sex per se account for the apparent sex differences in callosal morphology. Comparing callosal dimensions between men and women matched for overall brain size may clarify the true contribution of biological sex, as any observed group difference should indicate pure sex effects. We thus examined callosal morphology in 24 male and 24 female brains carefully matched for overall size. In addition, we selected 24 extremely large male brains and 24 extremely small female brains to explore if observed sex effects might vary depending on the degree to which male and female groups differed in brain size. Using the individual T1-weighted brain images (n=96), we delineated the corpus callosum at midline and applied a well-validated surface-based mesh-modeling approach to compare callosal thickness at 100 equidistant points between groups determined by brain size and sex. The corpus callosum was always thicker in men than in women. However, this callosal sex difference was strongly determined by the cerebral sex difference overall. That is, the larger the discrepancy in brain size between men and women, the more pronounced the sex difference in callosal thickness, with hardly any callosal differences remaining between brain-size matched men and women. Altogether, these findings suggest that individual differences in brain size account for apparent sex differences in the anatomy of the corpus callosum.
    NeuroImage 09/2013; · 6.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Our goal is to establish a science of the individual, grounded in dynamic systems, and focused on the analysis of individual variability. Our argument is that individuals behave, learn, and develop in distinctive ways, showing patterns of variability that are not captured by models based on statistical averages. As such, any meaningful attempt to develop a science of the individual necessarily begins with an account of the individual variability that is pervasive in all aspects of behavior, and at all levels of analysis. Using examples from fields as diverse as education and medicine, we show how starting with individual variability, not statistical averages, helped researchers discover two sources of ordered variability—pathways and contexts—that have implications for theory, research, and practice in multiple disciplines. We conclude by discussing three broad challenges—data, models, and the nature of science—that must be addressed to ensure that the science of the individual reaches its full potential.
    Mind Brain and Education 09/2013; 7(3). · 1.35 Impact Factor


Available from