, Volume 210, Issue 5-6, pp 343-352
Date: 06 Oct 2005

Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps

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Abstract

Probabilistic maps of neocortical areas and subcortical fiber tracts, warped to a common reference brain, have been published using microscopic architectonic parcellations in ten human postmortem brains. The maps have been successfully applied as topographical references for the anatomical localization of activations observed in functional imaging studies. Here, for the first time, we present stereotaxic, probabilistic maps of the hippocampus, the amygdala and the entorhinal cortex and some of their subdivisions. Cytoarchitectonic mapping was performed in serial, cell-body stained histological sections. The positions and the extent of cytoarchitectonically defined structures were traced in digitized histological sections, 3-D reconstructed and warped to the reference space of the MNI single subject brain using both linear and non-linear elastic tools of alignment. The probability maps and volumes of all structures were calculated. The precise localization of the borders of the mapped regions cannot be predicted consistently by macroanatomical landmarks. Many borders, e.g. between the subiculum and entorhinal cortex, subiculum and Cornu ammonis, and amygdala and hippocampus, do not match sulcal landmarks such as the bottom of a sulcus. Only microscopic observation enables the precise localization of the borders of these brain regions. The superposition of the cytoarchitectonic maps in the common spatial reference system shows a considerably lower degree of intersubject variability in size and position of the allocortical structures and nuclei than the previously delineated neocortical areas. For the first time, the present observations provide cytoarchitectonically verified maps of the human amygdala, hippocampus and entorhinal cortex, which take into account the stereotaxic position of the brain structures as well as intersubject variability. We believe that these maps are efficient tools for the precise microstructural localization of fMRI, PET and anatomical MR data, both in healthy and pathologically altered brains.