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Existing cytoarchitectonic maps of the human and macaque posterior occipital cortex differ in the number of areas they display, thus hampering identification of homolog structures. We applied quantitative in vitro receptor autoradiography to characterize the receptor architecture of the primary visual and early extrastriate cortex in macaque and human brains, using previously published cytoarchitectonic criteria as starting point of our analysis. We identified 8 receptor architectonically distinct areas in the macaque brain (mV1d, mV1v, mV2d, mV2v, mV3d, mV3v, mV3A, mV4v), and their respective counterpart areas in the human brain (hV1d, hV1v, hV2d, hV2v, hV3d, hV3v, hV3A, hV4v). Mean densities of 14 neurotransmitter receptors were quantified in each area, and ensuing receptor fingerprints used for multivariate analyses. The 1st principal component segregated macaque and human early visual areas differ. However, the 2nd principal component showed that within each species, area-specific differences in receptor fingerprints were associated with the hierarchical processing level of each area. Subdivisions of V2 and V3 were found to cluster together in both species and were segregated from subdivisions of V1 and from V4v. Thus, comparative studies like this provide valuable architectonic insights into how differences in underlying microstructure impact evolutionary changes in functional processing of the primate brain and, at the same time, provide strong arguments for use of macaque monkey brain as a suitable animal model for translational studies. [ABSTRACT FROM AUTHOR]

• Cyto- and receptor-based parcellation of macaque inferior parietal lobe (IPL). • Caudo-rostral gradients found in the architectonic organization of IPL areas. • Hierarchical analysis segregated IPL areas into rostral and caudal clusters. • Novel insights into homologies between human and macaque IPL areas. The macaque monkey inferior parietal lobe (IPL) is a structurally heterogeneous brain region, although the number of areas it contains and the anatomical/functional relationship of identified subdivisions remains controversial. Neurotransmitter receptor distribution patterns not only reveal the position of the cortical borders, but also segregate areas associated to different functional systems. Thus we carried out a multimodal quantitative analysis of the cyto- and receptor architecture of the macaque IPL to determine the number and extent of distinct areas it encompasses. We identified four areas on the IPL convexity arranged in a caudo-rostral sequence, as well as two areas in the parietal operculum, which we projected onto the Yerkes19 surface. We found rostral areas to have relatively smaller receptor fingerprints than the caudal ones, which is in an agreement with the functional gradient along the caudo-rostral axis described in previous studies. The hierarchical analysis segregated IPL areas into two clusters: the caudal one, contains areas involved in multisensory integration and visual-motor functions, and rostral cluster, encompasses areas active during motor planning and action-related functions. The results of the present study provide novel insights into clarifying the homologies between human and macaque IPL areas. The ensuing 3D map of the macaque IPL, and the receptor fingerprints are made publicly available to the neuroscientific community via the Human Brain Project and BALSA repositories for future cyto- and/or receptor architectonically driven analyses of functional imaging studies in non-human primates. [ABSTRACT FROM AUTHOR]

• Multimodal analysis of macaque motor and premotor cortex reveals novel parcellation • 3D atlas with cyto- and multireceptor architectonic features of 16 (pre)motor areas • Primary motor area 4 is cyto- and receptor architectonically heterogeneous • (Pre)motor areas differ in their functional connectivity fingerprints In the present study we reevaluated the parcellation scheme of the macaque frontal agranular cortex by implementing quantitative cytoarchitectonic and multireceptor analyses, with the purpose to integrate and reconcile the discrepancies between previously published maps of this region. We applied an observer-independent and statistically testable approach to determine the position of cytoarchitectonic borders. Analysis of the regional and laminar distribution patterns of 13 different transmitter receptors confirmed the position of cytoarchitectonically identified borders. Receptor densities were extracted from each area and visualized as its "receptor fingerprint". Hierarchical and principal components analyses were conducted to detect clusters of areas according to the degree of (dis)similarity of their fingerprints. Finally, functional connectivity pattern of each identified area was analyzed with areas of prefrontal, cingulate, somatosensory and lateral parietal cortex and the results were depicted as "connectivity fingerprints" and seed-to-vertex connectivity maps. We identified 16 cyto- and receptor architectonically distinct areas, including novel subdivisions of the primary motor area 4 (i.e. 4a, 4p, 4m) and of premotor areas F4 (i.e. F4s, F4d, F4v), F5 (i.e. F5s, F5d, F5v) and F7 (i.e. F7d, F7i, F7s). Multivariate analyses of receptor fingerprints revealed three clusters, which first segregated the subdivisions of area 4 with F4d and F4s from the remaining premotor areas, then separated ventrolateral from dorsolateral and medial premotor areas. The functional connectivity analysis revealed that medial and dorsolateral premotor and motor areas show stronger functional connectivity with areas involved in visual processing, whereas 4p and ventrolateral premotor areas presented a stronger functional connectivity with areas involved in somatomotor responses. For the first time, we provide a 3D atlas integrating cyto- and multi-receptor architectonic features of the macaque motor and premotor cortex. This atlas constitutes a valuable resource for the analysis of functional experiments carried out with non-human primates, for modeling approaches with realistic synaptic dynamics, as well as to provide insights into how brain functions have developed by changes in the underlying microstructure and encoding strategies during evolution. Image, graphical abstract [ABSTRACT FROM AUTHOR]