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A probabilistic atlas of the human brain: theory and rationale for
its development. The International Consortium for Brain Mapping (ICBM)
Source: Neuroimage 1995 Jun;2(2):89-101.
Author: Mazziotta JC, Toga AW, Evans A, Fox P, Lancaster J.
PubMed ID: 9343592
Abstract:
This article reviews the theory and rationale for defining a probabilistic atlas derived from a large series of subjects, representative of the entire species, with retention of information about variability. Such a project must take on the problems inherent in dealing with biologically variable structure and function but, when successful, will provide a system that is realistic in its complexity, has defined accuracy and errors, and that, as a benefit, contributes new neurobiological information. That atlas is envisioned to be both visualizable (e.g., recognizable brain images) and quantitative (e.g., tabular databases). Digital in its composition, the atlas, and the tools to enter and retrieve data from it, produce probabilistic reponses to queries. That is, for a given location identified in the reference space, the atlas will produce probability distributinos and confidence limits for structure identification, functional variables (e.g., blood flow, metabolism, receptor density, etc.), clinical information (e.g., deficits associated with lesions at the site, behavioral states that augment functions like blood flow at the site, etc.), and bibliographic data. By defining a subpopulation of the database contents in a given query, probabilites would shift to reflect a more constrained subset of the entire population.
Source: Neuroimage 1995 Jun;2(2):89-101.
Author: Mazziotta JC, Toga AW, Evans A, Fox P, Lancaster J.
PubMed ID: 9343592
Abstract:
This article reviews the theory and rationale for defining a probabilistic atlas derived from a large series of subjects, representative of the entire species, with retention of information about variability. Such a project must take on the problems inherent in dealing with biologically variable structure and function but, when successful, will provide a system that is realistic in its complexity, has defined accuracy and errors, and that, as a benefit, contributes new neurobiological information. That atlas is envisioned to be both visualizable (e.g., recognizable brain images) and quantitative (e.g., tabular databases). Digital in its composition, the atlas, and the tools to enter and retrieve data from it, produce probabilistic reponses to queries. That is, for a given location identified in the reference space, the atlas will produce probability distributinos and confidence limits for structure identification, functional variables (e.g., blood flow, metabolism, receptor density, etc.), clinical information (e.g., deficits associated with lesions at the site, behavioral states that augment functions like blood flow at the site, etc.), and bibliographic data. By defining a subpopulation of the database contents in a given query, probabilites would shift to reflect a more constrained subset of the entire population.