An architectonic type principle integrates macroscopic cortico-cortical connections with intrinsic cortical circuits of the primate brain

Abstract

The connections linking neurons within and between cerebral cortical areas form a multiscale network for communication. We review recent work relating essential features of cortico-cortical connections, such as their existence and laminar origins and terminations, to fundamental structural parameters of cortical areas, such as their distance, similarity in cytoarchitecture, defined by lamination or neuronal density, and other macroscopic and microscopic structural features. These analyses demonstrate the presence of an architectonic type principle. Across species and cortices, the essential features of cortico-cortical connections vary consistently and strongly with the cytoarchitectonic similarity of cortical areas. By contrast, in multivariate analyses such relations were not found consistently for distance, similarity of cortical thickness, or cellular morphology. Gradients of laminar cortical differentiation, as reflected in overall neuronal density, also correspond to regional variations of cellular features, forming a spatially ordered natural axis of concerted architectonic and connectional changes across the cortical sheet. The robustness of findings across mammalian brains allows cross-species predictions of the existence and laminar patterns of projections, including estimates for the human brain that are not yet available experimentally. The architectonic type principle integrates cortical connectivity and architecture across scales, with implications for computational explorations of cortical physiology and developmental mechanisms.

Keywords: Cortical connectome; Cortical structural gradients; Cytoarchitecture; Wiring principles.

Figure 1.

Principles of cortical wiring integrate regularities of cortical architecture, connectivity, and function through mechanistic explanations. Connections create functions of brain areas, and functional interactions among areas, from the structural substrate of the brain, and specifically the cortical sheet. In particular, areas are linked through connections which have a laminar composition that is appropriate for the laminar microenvironment within the respective areas as well as the type of information exchange between these areas. Thus, local cortical architecture, the connection features of a cortical area, and an area’s functional role within the cortical network are tightly intertwined. Adapted from Beul and Hilgetag (2019).

Figure 2.

Architectonic type principle across species. Upper panels: Maps of the cat and macaque cortex, indicating the variation of architectonic differentiation across the cortex of these two species. Differentiation is represented as architectonic type in the cat cortex and as neuron density in the macaque cortex. Lower panels: Visualization of cortico-cortical connections in the cat and macaque cortex. Cat connections are shown as collated in Scannell et al. (1995); macaque connections are shown as published by Markov, Ercsey-Ravasz, et al. (2014). Gray rings correspond to degree of architectonic differentiation (determined as cortical type for the cat and by neuron density for the macaque) and cortical areas are placed accordingly, with differentiation increasing from center to periphery. Projections are color coded according to the difference in architectonic differentiation between connected areas. Node sizes indicate the areas’ degree (that is, the number of connections associated with them). For the cat cortex, ordinal projection strength (sparse, intermediate, or dense) is coded by increasing projection width and nodes are grouped and color coded according to anatomical modules as indicated. Hub-module areas, as classified by Zamora-López et al. (2010) in the cat and Ercsey-Ravasz et al. (2013) in the macaque, are marked by a white outline or red fill, respectively. Panels adapted from Beul et al. (2017, 2015).

Figure 3.

Cytoarchitectonic similarity relates to the existence of connections in a species-specific manner. (A) Increasing cytoarchitectonic dissimilarity of cortical areas results in a decrease of the probability of the existence of a connection. This decrease is more pronounced for the cat when compared with the mouse, as indicated by the larger probability decrease (shaded areas) for the same increase of cytoarchitectonic dissimilarity. (B) Same relation as in (A), but for the comparison of mouse versus macaque monkey. The shaded areas highlight the differences of probability of existence of a connection with an increase of cytoarchitectonic dissimilarity in the different species. Note that the illustrated differences of probability of existence can be visually demonstrated in other intervals, such as 0.4–0.5 or 0.7–0.8. The decrease of the probability of the existence of a connection is more pronounced for the macaque monkey when compared with the mouse. (C) Same relation as in (A), but for the comparison of cat versus macaque monkey. In this comparison, no species-specific differences of the effect of cytoarchitectonic similarity on the probability of connections were observed. (D) Brain size and phylogenetic distance of the mouse, macaque monkey, and cat. Adapted from Goulas et al. (2019).

Figure 4.

Integration of cortical macro- and microarchitecture with cortical connections. Less architectonically differentiated, agranular, cortical areas (yellow) are characterized by lower neuron density and different morphology of layer III pyramidal cells than more strongly differentiated, eulaminate, areas (dark green), with gradual changes across the spectrum. (A) Macroscopic and microscopic architectonic features show concerted changes along spatial cortical gradients, indicating a natural axis of cortical organization. In particular, higher neuron density tends to correlate with smaller cross sections of the soma and the dendritic tree as well as with lower total spine count and lower peak spine density. (B) Relations of architectonic types with connection features. Within cortical areas, the ratio of supra- versus infragranular soma size of projection neurons tends to increase as one transitions from less to more differentiated areas (externopyramidization; Goulas et al., 2018). Also note that projection neurons are displayed with relatively larger soma cross section than nonprojection neurons in the same cortical area and layer. Importantly, connections exist predominantly between areas of similar cortical type, and agranular and dysgranular regions (yellow) tend to form more connections than eulaminate regions (dark green). Hence agranular and dysgranular regions tend to be part of the network core, while eulaminate regions tend to be part of the network periphery (cf. Figure 2). Moreover, laminar patterns of projection origins are related to differences in architectonic differentiation. Connections between areas of distinct differentiation show a skewed unilaminar projection pattern, with projections originating predominantly in the infragranular or supragranular layers depending on the direction of the projection (agranular to eulaminate projections and eulaminate to agranular projections, respectively), while connections between areas of similar architectonic differentiation show a bilaminar projection origin pattern (connections between middle panels), where the dominating laminar compartment again depends on the connected areas’ relative differentiation. In sum, there are concurrent changes of macro- and microstructural cellular and connectional features across the cortical sheet, forming spatially ordered gradients, confirming and expanding observations from classic neuroanatomy studies (gradation principle of Sanides, 1962). Panels adapted from Beul and Hilgetag (2019).

Figure 5.

Developmental origins of the architectonic type principle. Summary of computational modeling of the ontogenetic development of cortical architecture and connections (Beul et al., 2018). The simulations indicate that the presence of two spatial origins of neurogenesis, resulting in two neurogenetic (temporal) and architectonic gradients, is necessary for the close correspondence of the in silico model to the empirical relations between connectivity and architectonic differentiation. Importantly, the empirically observed relations are replicated in silico only if the less-to-more differentiated architectonic gradients align with early-to-late ontogenetic gradients. Hence, the suggested mechanism is consistent with correspondence of time of neurogenesis to architectonic differentiation (e.g., Dombrowski, Hilgetag, & Barbas, 2001) and a dual origin of the cerebral cortex (Pandya, Seltzer, Petrides, & Cipolloni, ; Sanides, 1962).

Figure 6.

The architectonic type principle enables the generation of large-scale cortical models that integrate microscopic and macroscopic cortical architecture and connections. Schematic representation of a multiarea spiking model of macaque vision-related cortex, with laminar patterns of cortico-cortical connectivity determined in part from relative neuron densities of connected areas. Interarea and local connectivity together form polysynaptic pathways through the network. Figure reproduced from Schmidt, Bakker, Hilgetag, et al. (2018).