Cytoarchitectural differences are a key determinant of laminar projection origins in the visual cortex
Introduction
Laminar origins and terminations of connections between areas of the mammalian cerebral cortex show a remarkable regularity. This regularity is most clearly demonstrated by the fact that the areas of sensory (e.g., visual, somatosensory) and motor cortex can been arranged into largely consistent global schemes, in which laminar connectivity patterns believed to signify projections in one of three possible directions (“forward,” “backward” or “lateral”) are repeated across the whole arrangement (Felleman and Van Essen, 1991, Hilgetag et al., 2000b, Scannell et al., 1995). The classification of “forward,” “backward,” and “lateral” projections is based on the predominant layers of projection origin and termination. Projections have been labeled “forward” if they originate mainly from neurons in upper cortical layers (II + III) and terminate in the granular layer (IV) of their target, while complementary “backward” projections arise mainly from deep cortical layers (V + VI) and terminate outside layer IV of the target area (Rockland and Pandya, 1979). Finally, “lateral” projections originate in a more bilaminar pattern involving roughly equal contributions from upper and deep layers and terminate across all layers, including layer IV (Felleman and Van Essen, 1991). While this classification was originally applied to connections of primate visual areas 17, 18 and 19 (Rockland and Pandya, 1979), later approaches extended the scheme to additional extrastriate cortices and other types of primate sensory cortex (Felleman and Van Essen, 1991), as well as visual cortex in the cat (Felleman and Van Essen, 1991, Scannell et al., 1995) and rat (Coogan and Burkhalter, 1993).
Quantitative studies have demonstrated that there are also gradual shifts in the laminar projection origins within each of these categories. For example, the relative contribution of upper (supragranular) layers to a “forward” projection may vary from 100% to little more than 50% (Barone et al., 2000, Grant and Hilgetag, 2005, Vezoli et al., 2004) with the remainder coming from the deep layers. Moreover, there exists considerable variability of projection patterns at the level of individual neurons (Rockland, 1997, Rockland, 2003).
What explains the systematic but varied patterns of laminar projection origins? Three principal models have been proposed. First, the graded distribution may depend on the hierarchical level difference between the linked areas in global cortical hierarchies (Barone et al., 2000, Vezoli et al., 2004). Such hierarchical schemes (Felleman and Van Essen, 1991) are popular summaries of the organization of cortical association fibers and their putative function, despite caveats for their construction (Hilgetag et al., 1996) and interpretation (Hegde and Felleman, 2007). In the hierarchical model (Barone et al., 2000) it is argued that projections with a strong laminar bias of origin (i.e., close to 100% upper or deep layer) occur between areas occupying the top and bottom levels of a global hierarchy, while projections of more equal laminar origin (i.e., approximately 50% bilaminar) occur between areas on the same or adjacent hierarchical levels.
In the second, structural model it is proposed that graded laminar patterns derive from differences in the cytoarchitectonic differentiation of the cortical areas forming the source and target of a given projection (Barbas, 1986, Barbas and Rempel-Clower, 1997, Medalla and Barbas, 2006, Rempel-Clower and Barbas, 2000). Specifically, projections from structurally more differentiated to less differentiated areas arise predominantly from the upper cortical layers, while projections in the reverse direction originate mainly from deep layers, and projections between architecturally similar areas possess a balanced bilaminar character (Barbas, 1986).
Finally, it has been an influential idea that the existence or absence of inter-connections between cortical areas (Klyachko and Stevens, 2003, Young, 1992) as well as laminar projection features (Salin and Bullier, 1995) vary systematically with physical distance and the number of intervening area borders.
So far, these different models have been primarily tested for connections of the visual cortex (hierarchical model) or prefrontal cortex (structural model) or both (distance model) in the primate brain. Here an opportunity arose to test all three models on the same quantitative material concerning both the relative densities (i.e., strength) and laminar origins of widespread projections to cat extrastriate visual areas (Grant and Hilgetag, 2005, Hilgetag and Grant, 2000). This allowed us to directly evaluate the selective applicability of these concepts for graded laminar connections in another class of mammal with a well developed cerebral cortex.
Section snippets
Projection data
Quantitative measures of relative projection densities and laminar origins were based on published connection tracing data derived from WGA-HRP injections in the vicinity of the middle suprasylvian sulcus (MSS) in 11 adult cats; 10 with single injections in different areas (PMLS, AMLS, PLLS) of the lateral suprasylvian (LS) cortex, and one with a similar injection in area 21a which adjoins area PMLS caudally. Each injection resulted in the labeling of projection neurons in 13–19 identified
General observations
By application of cluster analyses to the quantitative data used in the current work, we previously found that there are three discrete classes of laminar origin in the projections to the cat′s MSS cortex (Grant and Hilgetag, 2005). Representatives of each of these classes can be seen (in Fig. 3) to conform to projection patterns typically described as “forward” (from area 17), “lateral” (area 20a) or “backward” (area 20b). Each of the classes, however, also comprised a broad and well-populated
Discussion
Several models have been proposed to account for the density and laminar patterns of connections between different areas of the cerebral cortex, motivated by the hope that a consistent summary scheme will also offer clues to the functional organization of the system (Hegde and Felleman, 2007, Van Essen et al., 1992, Zeki and Shipp, 1988). One popular scheme is the hierarchical model, exemplified by Felleman and Van Esssen′s (1991) diagram of visual cortical connections in the macaque monkey,
Acknowledgment
We thank R. J. Rushmore for his helpful comments on the manuscript.
References (63)
- et al.
Mapping the matrix: the ways of neocortex
Neuron
(2007) - et al.
Lateral suprasylvian visual cortex is activated earlier than or synchronously with primary visual cortex in the cat
Neurosci. Res.
(1996) - et al.
Eye movement-related activities in cells of the lateral suprasylvian cortex of the cat
Neurosci. Lett.
(1983) - et al.
Simple and complex visual motion response properties in the anterior medial bank of the lateral suprasylvian cortex
Neuroscience
(2004) - et al.
Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey
Brain Res.
(1979) Influence of areas 17, 18, and 19 on receptive-field properties of neurons in the cat's posteromedial lateral suprasylvian visual cortex
Prog. Brain Res.
(1988)- et al.
Visual receptive field properties in the posterior suprasylvian cortex of the cat: a comparison between the areas PMLS and PLLS
Vis. Res
(1987) Pattern in the laminar origin of corticocortical connections
J. Comp. Neurol.
(1986)- et al.
Cortical structure predicts the pattern of corticocortical connections
Cereb. Cortex
(1997) - et al.
Parallel organization of contralateral and ipsilateral prefrontal cortical projections in the rhesus monkey
BMC Neurosci.
(2005)
Laminar distribution of neurons in extrastriate areas projecting to visual areas V1 and V4 correlates with the hierarchical rank and indicates the operation of a distance rule
J. Neurosci.
Projections from V1 to lateral suprasylvian cortex: an efferent pathway in the cat's visual cortex that originates preferentially from CO blob columns
Vis. Neurosci.
Hierarchical organization of areas in rat visual cortex
J. Neurosci.
The timing of processing along the visual pathway in the cat
NeuroReport
Areas PMLS and 21a of cat visual cortex: two functionally distinct areas
Cereb. Cortex
Ipsilateral corticocortical projections to the primary and middle temporal visual areas of the primate cerebral cortex: area-specific variations in the morphology of connectionally identified pyramidal cells
Eur. J. NeuroSci.
Distributed hierarchical processing in the primate cerebral cortex
Cereb. Cortex
A theory of cortical responses
Philos. Trans. R. Soc. Lond. B Biol. Sci.
Graded classes of cortical connections: quantitative analyses of laminar projections to motion areas of cat extrastriate cortex
Eur. J. NeuroSci.
Visuotopic organization of the lateral suprasylvian area and of an adjacent area of the ectosylvian gyrus of cat cortex: a physiological and connectional study
Vis. Neurosci.
A statistical analysis of information-processing properties of lamina-specific cortical microcircuit models
Cereb. Cortex
Reappraising the functional implications of the primate visual anatomical hierarchy
Neuroscientist
Uniformity, specificity and variability of corticocortical connectivity
Philos. Trans. R. Soc. Lond. B Biol. Sci.
Indeterminate organization of the visual system
Science
Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat
Philos. Trans. R. Soc. Lond. B Biol. Sci.
Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor
Philos. Trans. R. Soc. Lond. B Biol. Sci.
Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems
PLoS Comput. Biol.
Connectivity optimization and the positioning of cortical areas
Proc. Natl. Acad. Sci. U. S. A.
Response properties of PMLS and PLLS neurons to simulated optic flow patterns
Eur. J. NeuroSci.
Perceptual and cognitive visual functions of parietal and temporal cortices in the cat
Cereb. Cortex
Diversity of laminar connections linking periarcuate and lateral intraparietal areas depends on cortical structure
Eur. J. NeuroSci.
Cited by (59)
Neuron density fundamentally relates to architecture and connectivity of the primate cerebral cortex
2019, NeuroImageCitation Excerpt :Specifically, for each projection, NSG% was computed as the number of neurons labeled in supragranular layers divided by the sum of neurons labeled in supragranular and infragranular layers. To relate NSG% to the undirected measure of geodesic distance, we also transformed it to an undirected measure of inequality in laminar patterns, |NSG%|, where |NSG%| = |NSG% - 50| * 2 (cf. Hilgetag and Grant, 2010; Beul et al., 2015). Values of NSG% around 0% and 100%, thus, translated to larger values of |NSG%|, indicating a more pronounced inequality in the distribution of origins of projection neurons between infra- and supragranular layers and hence deviation from a columnar (bilaminar) pattern of projection origins.
Cortical Gradients and Laminar Projections in Mammals
2018, Trends in NeurosciencesMultimodal Connectomics in Psychiatry: Bridging Scales From Micro to Macro
2018, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging