ReviewBrain templates and atlases
Introduction
The creation and application of atlases for brain research are now widespread (see Cabezas et al., 2011 for a comprehensive review). Here we focus on the historical evolution of those atlases and strategies that have particular relevance for the fMRI community. The core concept within the field of brain mapping is the use of a standardized 3D coordinate frame for the analysis and reporting of neuroimaging experiments. This apparently trivial device has had a profound impact on the study of functional neuroanatomy and the practice of neuroscience research in general. The early pioneering works of Brodmann, 1909, Brodmann, 1914, Brodmann, 1960, Flechsig (1920), von Economo and Koskinas (1925), Vogt and Vogt (1919) and Sarkisov et al. (1955) to map the cyto- and myelo-architectural landscape of the human cortex were based on painstaking visual inspection and characterization of a few observable cellular properties (packing density, cell shape, laminar organization). They were typically carried out on single brains and cortical parcellation schemes were largely restricted to the gyral surface, ignoring the two-thirds of cortical area buried in the sulcal folds (Zilles and Amunts, 2010). Neuroimaging techniques evolved over the last 20 years have allowed neuroscientists to re-visit the issue of mapping the human brain, such that a modern brain atlas is now expressed as a digital database that can capture the spatio-temporal distribution of a multitude of physiological and anatomical metrics. Furthermore, it allows for a quantitative characterization of the (i) normal variability in those metrics across a population, (ii) the relationship between those metrics and behavioral performance and (iii) the detection of subtle changes associated with disease, genotype, gender or demographics.
Section snippets
Whole brain adult atlases
The origins of modern brain mapping lie with the seminal work of Jean Talairach (Talairach et al., 1967), who developed a 3D coordinate space to assist deep-brain surgical techniques. This was later updated by Talairach and Tournoux (1988) as a printed atlas for guidance of deep-brain stereotactic procedures. The earliest application of Talairach space for brain mapping was by Fox et al. (1985) who used it to map the 3D coordinates of activation foci from PET experiments in different
Diffeomorphism and anatomical variability
The 3D spatial mapping function between individual brains and a template brain may take many forms: from a simple, linear transformation (e.g. Collins et al., 1994, Woods et al., 1993) to more sophisticated non-linear approaches. While the linear approaches have the advantage of simplicity, and therefore easier comparability across studies from different laboratories, they exhibit poorer anatomical correspondence than higher-dimensional approaches. Fig. 3a summarizes schematically the
Current and future trends
The progression of brain atlases over the last 20 years from printed reference textbooks to digital, multivariate, multidimensional, statistical maps has been quite staggering. There appears to be no end in sight as computational tools become ever-more powerful and accessible, and data sharing, a common practice of the neuroimaging community. The modern brain atlas is now an engine for meta-analysis of information from all corners of neuroscience. We can expect the next decade to bring forth a
Conclusion
The combination of the traditional atlas metrics of classical neuroanatomy with maps of gene expression and connectivity, potentially with a temporal component, will offer entirely novel perspectives on brain organization. Capturing the population variance of these multivariate attribute maps in the form of probabilistic atlases, amenable to statistical analysis, will revolutionize our understanding of functional neuroanatomy and the changes associated with development, aging, learning and
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